[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Christine Poerschke updated SOLR-8542: -- Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously [presented by the authors at Lucene/Solr Revolution 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. Solr Reference Guide documentation: * https://cwiki.apache.org/confluence/display/solr/Learning+To+Rank Source code and README files: * [solr/contrib/ltr|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr] * [solr/contrib/ltr/example|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr/example] was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously [presented by the authors at Lucene/Solr Revolution 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. Solr Reference Guide documentation: * https://cwiki.apache.org/confluence/display/solr/Result+Reranking Source code and README files: * [solr/contrib/ltr|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr] * [solr/contrib/ltr/example|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr/example] > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke > Fix For: master (7.0), 6.4 > > Attachments: SOLR-8542-branch_5x.patch, SOLR-8542.patch, > SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously [presented by the authors at Lucene/Solr > Revolution > 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. > > Solr Reference Guide documentation: > * https://cwiki.apache.org/confluence/display/solr/Learning+To+Rank > Source code and README files: > * > [solr/contrib/ltr|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr] > * > [solr/contrib/ltr/example|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr/example] -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Christine Poerschke updated SOLR-8542: -- Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously [presented by the authors at Lucene/Solr Revolution 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. Solr Reference Guide documentation: * https://cwiki.apache.org/confluence/display/solr/Result+Reranking Source code and README files: * [solr/contrib/ltr|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr] * [solr/contrib/ltr/example|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr/example] was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously [presented by the authors at Lucene/Solr Revolution 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. --- Solr Reference Guide documentation: * https://cwiki.apache.org/confluence/display/solr/Result+Reranking Source code and README files: * [solr/contrib/ltr|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr] * [solr/contrib/ltr/example|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr/example] > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke > Fix For: master (7.0), 6.4 > > Attachments: SOLR-8542-branch_5x.patch, SOLR-8542-trunk.patch, > SOLR-8542.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously [presented by the authors at Lucene/Solr > Revolution > 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. > > Solr Reference Guide documentation: > * https://cwiki.apache.org/confluence/display/solr/Result+Reranking > Source code and README files: > * > [solr/contrib/ltr|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr] > * > [solr/contrib/ltr/example|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr/example] -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Christine Poerschke updated SOLR-8542: -- Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously [presented by the authors at Lucene/Solr Revolution 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. --- Solr Reference Guide documentation: * https://cwiki.apache.org/confluence/display/solr/Result+Reranking Source code and README files: * [solr/contrib/ltr|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr] * [solr/contrib/ltr/example|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr/example] was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously [presented by the authors at Lucene/Solr Revolution 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. [Read through the README|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-release/solr/contrib/ltr] for a tutorial on using the plugin, in addition to how to train your own external model. > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke > Fix For: master (7.0), 6.4 > > Attachments: SOLR-8542-branch_5x.patch, SOLR-8542-trunk.patch, > SOLR-8542.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously [presented by the authors at Lucene/Solr > Revolution > 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. > --- > Solr Reference Guide documentation: > * https://cwiki.apache.org/confluence/display/solr/Result+Reranking > Source code and README files: > * > [solr/contrib/ltr|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr] > * > [solr/contrib/ltr/example|https://github.com/apache/lucene-solr/blob/master/solr/contrib/ltr/example] -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Christine Poerschke updated SOLR-8542: -- Fix Version/s: 6.4 master (7.0) > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke > Fix For: master (7.0), 6.4 > > Attachments: SOLR-8542-branch_5x.patch, SOLR-8542-trunk.patch, > SOLR-8542.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously [presented by the authors at Lucene/Solr > Revolution > 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. > [Read through the > README|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-release/solr/contrib/ltr] > for a tutorial on using the plugin, in addition to how to train your own > external model. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Christine Poerschke updated SOLR-8542: -- Priority: Major (was: Minor) > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke > Fix For: master (7.0), 6.4 > > Attachments: SOLR-8542-branch_5x.patch, SOLR-8542-trunk.patch, > SOLR-8542.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously [presented by the authors at Lucene/Solr > Revolution > 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. > [Read through the > README|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-release/solr/contrib/ltr] > for a tutorial on using the plugin, in addition to how to train your own > external model. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Christine Poerschke updated SOLR-8542: -- Attachment: SOLR-8542.patch Attaching patch generated as diff between 'master' and https://github.com/apache/lucene-solr/tree/jira/solr-8542-v2 - master commit to follow shortly. > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke >Priority: Minor > Attachments: SOLR-8542-branch_5x.patch, SOLR-8542-trunk.patch, > SOLR-8542.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously [presented by the authors at Lucene/Solr > Revolution > 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. > [Read through the > README|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-release/solr/contrib/ltr] > for a tutorial on using the plugin, in addition to how to train your own > external model. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously [presented by the authors at Lucene/Solr Revolution 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. [Read through the README|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-release/solr/contrib/ltr] for a tutorial on using the plugin, in addition to how to train your own external model. was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, David Grohmann and Diego Ceccarelli. [Read through the README|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-release/solr/contrib/ltr] for a tutorial on using the plugin, in addition to how to train your own external model. > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke >Priority: Minor > Attachments: SOLR-8542-branch_5x.patch, SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously [presented by the authors at Lucene/Solr > Revolution > 2015|http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp]. > [Read through the > README|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-release/solr/contrib/ltr] > for a tutorial on using the plugin, in addition to how to train your own > external model. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, David Grohmann and Diego Ceccarelli. [Read through the README|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-release/solr/contrib/ltr] for a tutorial on using the plugin, in addition to how to train your own external model. was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, David Grohmann and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! *access to the default feature store* http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ *access to the model store* http://localhost:8983/solr/techproducts/schema/mstore *perform a query using the model, and retrieve the features* http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke >Priority: Minor > Attachments: SOLR-8542-branch_5x.patch, SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( > http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp > ). > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > David Grohmann and Diego Ceccarelli. > [Read through the > README|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-release/solr/contrib/ltr] > for a tutorial on using the plugin, in addition to how to train your own > external model. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Diego Ceccarelli updated SOLR-8542: --- Attachment: (was: README.md) > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke >Priority: Minor > Attachments: SOLR-8542-branch_5x.patch, SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( > http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp > ). > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > David Grohmann and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. > h3. Test the plugin with solr/example/techproducts in 6 steps > Solr provides some simple example of indices. In order to test the plugin > with > the techproducts example please follow these steps > h4. 1. compile solr and the examples > cd solr > ant dist > ant example > h4. 2. run the example > ./bin/solr -e techproducts > h4. 3. stop it and install the plugin: > > ./bin/solr stop > mkdir example/techproducts/solr/techproducts/lib > cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar > example/techproducts/solr/techproducts/lib/ > cp contrib/ltr/example/solrconfig.xml > example/techproducts/solr/techproducts/conf/ > h4. 4. run the example again > > ./bin/solr -e techproducts > h4. 5. index some features and a model > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' > --data-binary "@./contrib/ltr/example/techproducts-features.json" -H > 'Content-type:application/json' > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' > --data-binary "@./contrib/ltr/example/techproducts-model.json" -H > 'Content-type:application/json' > h4. 6. have fun ! > *access to the default feature store* > http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ > *access to the model store* > http://localhost:8983/solr/techproducts/schema/mstore > *perform a query using the model, and retrieve the features* > http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Michael Nilsson updated SOLR-8542: -- Attachment: (was: README.md) > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke >Priority: Minor > Attachments: README.md, SOLR-8542-branch_5x.patch, > SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( > http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp > ). > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > David Grohmann and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. > h3. Test the plugin with solr/example/techproducts in 6 steps > Solr provides some simple example of indices. In order to test the plugin > with > the techproducts example please follow these steps > h4. 1. compile solr and the examples > cd solr > ant dist > ant example > h4. 2. run the example > ./bin/solr -e techproducts > h4. 3. stop it and install the plugin: > > ./bin/solr stop > mkdir example/techproducts/solr/techproducts/lib > cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar > example/techproducts/solr/techproducts/lib/ > cp contrib/ltr/example/solrconfig.xml > example/techproducts/solr/techproducts/conf/ > h4. 4. run the example again > > ./bin/solr -e techproducts > h4. 5. index some features and a model > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' > --data-binary "@./contrib/ltr/example/techproducts-features.json" -H > 'Content-type:application/json' > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' > --data-binary "@./contrib/ltr/example/techproducts-model.json" -H > 'Content-type:application/json' > h4. 6. have fun ! > *access to the default feature store* > http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ > *access to the model store* > http://localhost:8983/solr/techproducts/schema/mstore > *perform a query using the model, and retrieve the features* > http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, David Grohmann and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! *access to the default feature store* http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ *access to the model store* http://localhost:8983/solr/techproducts/schema/mstore *perform a query using the model, and retrieve the features* http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! *access to the default feature store* http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ *access to the model store* http://localhost:8983/solr/techproducts/schema/mstore *perform a query using the model, and retrieve the features* http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Diego Ceccarelli updated SOLR-8542: --- Attachment: (was: README.txt) > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke >Priority: Minor > Attachments: README.md, README.md, SOLR-8542-branch_5x.patch, > SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( > http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp > ). > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. > h3. Test the plugin with solr/example/techproducts in 6 steps > Solr provides some simple example of indices. In order to test the plugin > with > the techproducts example please follow these steps > h4. 1. compile solr and the examples > cd solr > ant dist > ant example > h4. 2. run the example > ./bin/solr -e techproducts > h4. 3. stop it and install the plugin: > > ./bin/solr stop > mkdir example/techproducts/solr/techproducts/lib > cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar > example/techproducts/solr/techproducts/lib/ > cp contrib/ltr/example/solrconfig.xml > example/techproducts/solr/techproducts/conf/ > h4. 4. run the example again > > ./bin/solr -e techproducts > h4. 5. index some features and a model > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' > --data-binary "@./contrib/ltr/example/techproducts-features.json" -H > 'Content-type:application/json' > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' > --data-binary "@./contrib/ltr/example/techproducts-model.json" -H > 'Content-type:application/json' > h4. 6. have fun ! > *access to the default feature store* > http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ > *access to the model store* > http://localhost:8983/solr/techproducts/schema/mstore > *perform a query using the model, and retrieve the features* > http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Diego Ceccarelli updated SOLR-8542: --- Attachment: README.md > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke >Priority: Minor > Attachments: README.md, README.md, SOLR-8542-branch_5x.patch, > SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( > http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp > ). > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. > h3. Test the plugin with solr/example/techproducts in 6 steps > Solr provides some simple example of indices. In order to test the plugin > with > the techproducts example please follow these steps > h4. 1. compile solr and the examples > cd solr > ant dist > ant example > h4. 2. run the example > ./bin/solr -e techproducts > h4. 3. stop it and install the plugin: > > ./bin/solr stop > mkdir example/techproducts/solr/techproducts/lib > cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar > example/techproducts/solr/techproducts/lib/ > cp contrib/ltr/example/solrconfig.xml > example/techproducts/solr/techproducts/conf/ > h4. 4. run the example again > > ./bin/solr -e techproducts > h4. 5. index some features and a model > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' > --data-binary "@./contrib/ltr/example/techproducts-features.json" -H > 'Content-type:application/json' > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' > --data-binary "@./contrib/ltr/example/techproducts-model.json" -H > 'Content-type:application/json' > h4. 6. have fun ! > *access to the default feature store* > http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ > *access to the model store* > http://localhost:8983/solr/techproducts/schema/mstore > *perform a query using the model, and retrieve the features* > http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Diego Ceccarelli updated SOLR-8542: --- Attachment: README.txt > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke >Priority: Minor > Attachments: README.md, README.txt, SOLR-8542-branch_5x.patch, > SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( > http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp > ). > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. > h3. Test the plugin with solr/example/techproducts in 6 steps > Solr provides some simple example of indices. In order to test the plugin > with > the techproducts example please follow these steps > h4. 1. compile solr and the examples > cd solr > ant dist > ant example > h4. 2. run the example > ./bin/solr -e techproducts > h4. 3. stop it and install the plugin: > > ./bin/solr stop > mkdir example/techproducts/solr/techproducts/lib > cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar > example/techproducts/solr/techproducts/lib/ > cp contrib/ltr/example/solrconfig.xml > example/techproducts/solr/techproducts/conf/ > h4. 4. run the example again > > ./bin/solr -e techproducts > h4. 5. index some features and a model > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' > --data-binary "@./contrib/ltr/example/techproducts-features.json" -H > 'Content-type:application/json' > curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' > --data-binary "@./contrib/ltr/example/techproducts-model.json" -H > 'Content-type:application/json' > h4. 6. have fun ! > *access to the default feature store* > http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ > *access to the model store* > http://localhost:8983/solr/techproducts/schema/mstore > *perform a query using the model, and retrieve the features* > http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! *access to the default feature store* http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ *access to the model store* http://localhost:8983/solr/techproducts/schema/mstore *perform a query using the model, and retrieve the features * http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! *strong*access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ *strong*access to the model store http://localhost:8983/solr/techproducts/schema/mstore *strong*perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr >
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! *strong*access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ *strong*access to the model store http://localhost:8983/solr/techproducts/schema/mstore *strong*perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr >
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! *access to the default feature store* http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ *access to the model store* http://localhost:8983/solr/techproducts/schema/mstore *perform a query using the model, and retrieve the features* http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! *access to the default feature store* http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ *access to the model store* http://localhost:8983/solr/techproducts/schema/mstore *perform a query using the model, and retrieve the features * http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feat
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-854
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps h4. 1. compile solr and the examples cd solr ant dist ant example h4. 2. run the example ./bin/solr -e techproducts h4. 3. stop it and install the plugin: ./bin/solr stop mkdir example/techproducts/solr/techproducts/lib cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ h4. 4. run the example again ./bin/solr -e techproducts h4. 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' h4. 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps 1. compile solr and the examples cd solr ant dist ant example 2. run the example ./bin/solr -e techproducts 3. stop it and install the plugin: ./bin/solr stop #create the lib folder mkdir example/techproducts/solr/techproducts/lib # install the plugin in the lib folder cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ # replace the original solrconfig with one importing all the ltr componenet cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ 4. run the example again ./bin/solr -e techproducts 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true > I
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. h3. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps 1. compile solr and the examples cd solr ant dist ant example 2. run the example ./bin/solr -e techproducts 3. stop it and install the plugin: ./bin/solr stop #create the lib folder mkdir example/techproducts/solr/techproducts/lib # install the plugin in the lib folder cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ # replace the original solrconfig with one importing all the ltr componenet cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ 4. run the example again ./bin/solr -e techproducts 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps 1. compile solr and the examples cd solr ant dist ant example 2. run the example ./bin/solr -e techproducts 3. stop it and install the plugin: ./bin/solr stop #create the lib folder mkdir example/techproducts/solr/techproducts/lib # install the plugin in the lib folder cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ # replace the original solrconfig with one importing all the ltr componenet cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ 4. run the example again ./bin/solr -e techproducts 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps 1. compile solr and the examples cd solr ant dist ant example 2. run the example ./bin/solr -e techproducts 3. stop it and install the plugin: ./bin/solr stop #create the lib folder mkdir example/techproducts/solr/techproducts/lib # install the plugin in the lib folder cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ # replace the original solrconfig with one importing all the ltr componenet cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ 4. run the example again ./bin/solr -e techproducts 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. ## Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps 1. compile solr and the examples cd solr ant dist ant example 2. run the example ./bin/solr -e techproducts 3. stop it and install the plugin: ./bin/solr stop #create the lib folder mkdir example/techproducts/solr/techproducts/lib # install the plugin in the lib folder cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ # replace the original solrconfig with one importing all the ltr componenet cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ 4. run the example again ./bin/solr -e techproducts 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. ## Test the plugin with solr/example/techproducts in 6 steps Solr provides some simple example of indices. In order to test the plugin with the techproducts example please follow these steps 1. compile solr and the examples cd solr ant dist ant example 2. run the example ./bin/solr -e techproducts 3. stop it and install the plugin: ./bin/solr stop #create the lib folder mkdir example/techproducts/solr/techproducts/lib # install the plugin in the lib folder cp build/contrib/ltr/lucene-ltr-6.0.0-SNAPSHOT.jar example/techproducts/solr/techproducts/lib/ # replace the original solrconfig with one importing all the ltr componenet cp contrib/ltr/example/solrconfig.xml example/techproducts/solr/techproducts/conf/ 4. run the example again ./bin/solr -e techproducts 5. index some features and a model curl -XPUT 'http://localhost:8983/solr/techproducts/schema/fstore' --data-binary "@./contrib/ltr/example/techproducts-features.json" -H 'Content-type:application/json' curl -XPUT 'http://localhost:8983/solr/techproducts/schema/mstore' --data-binary "@./contrib/ltr/example/techproducts-model.json" -H 'Content-type:application/json' 6. have fun ! # access to the default feature store http://localhost:8983/solr/techproducts/schema/fstore/_DEFAULT_ # access to the model store http://localhost:8983/solr/techproducts/schema/mstore # perform a query using the model, and retrieve the features http://localhost:8983/solr/techproducts/query?indent=on&q=test&wt=json&rq={!ltr%20model=svm%20reRankDocs=25%20efi.query=%27test%27}&fl=*,[features],price,score,name&fv=true was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Assignee: Christine Poerschke >Priority: Minor > Attachments: README.md, SOLR-8542-branch_5x.patch, > SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( > http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp > ). > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. > ## Test the plugin with solr/example/techproducts in 6 steps > Solr provides some simple example of indices. In order to test the plugin > with > the techproducts example please follow these steps > 1. compile solr and the examples > cd solr > ant dist > ant example > 2. run the example >
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Michael Nilsson updated SOLR-8542: -- Attachment: SOLR-8542-branch_5x.patch Attached a patch for the ltr contrib module against branch_5x as well > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Priority: Minor > Attachments: README.md, SOLR-8542-branch_5x.patch, > SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( > http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp > ). > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Description: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp ). The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. was: This is a ticket to integrate learning to rank machine learning models into Solr. Solr Learning to Rank (LTR) provides a way for you to extract features directly inside Solr for use in training a machine learned model. You can then deploy that model to Solr and use it to rerank your top X search results. This concept was previously presented by the authors at Lucene/Solr Revolution 2015 ( {http://www.slideshare.net/lucidworks/learning-to-rank-in- solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp} ) . The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, and Diego Ceccarelli. Any chance this could make it into a 5x release? We've also attached documentation as a github MD file, but are happy to convert to a desired format. > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Priority: Minor > Attachments: README.md, SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( > http://www.slideshare.net/lucidworks/learning-to-rank-in-solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp > ). > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate Learning to Rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joshua Pantony updated SOLR-8542: - Summary: Integrate Learning to Rank into Solr (was: Integrate learning to rank into Solr) > Integrate Learning to Rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Priority: Minor > Attachments: README.md, SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( {http://www.slideshare.net/lucidworks/learning-to-rank-in- > solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp} ) . > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org
[jira] [Updated] (SOLR-8542) Integrate learning to rank into Solr
[ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Michael Nilsson updated SOLR-8542: -- Attachment: README.md SOLR-8542-trunk.patch Attached the patch against trunk which contains our LTR code as a contrib module, plus a readme.md going over how to use it. > Integrate learning to rank into Solr > > > Key: SOLR-8542 > URL: https://issues.apache.org/jira/browse/SOLR-8542 > Project: Solr > Issue Type: New Feature >Reporter: Joshua Pantony >Priority: Minor > Attachments: README.md, SOLR-8542-trunk.patch > > > This is a ticket to integrate learning to rank machine learning models into > Solr. Solr Learning to Rank (LTR) provides a way for you to extract features > directly inside Solr for use in training a machine learned model. You can > then deploy that model to Solr and use it to rerank your top X search > results. This concept was previously presented by the authors at Lucene/Solr > Revolution 2015 ( {http://www.slideshare.net/lucidworks/learning-to-rank-in- > solr-presented-by-michael-nilsson-diego-ceccarelli-bloomberg-lp} ) . > The attached code was jointly worked on by Joshua Pantony, Michael Nilsson, > and Diego Ceccarelli. > Any chance this could make it into a 5x release? We've also attached > documentation as a github MD file, but are happy to convert to a desired > format. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: dev-unsubscr...@lucene.apache.org For additional commands, e-mail: dev-h...@lucene.apache.org