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Christine Poerschke commented on SOLR-8542: ------------------------------------------- The branch behind the https://github.com/apache/lucene-solr/pull/4 above is [master-ltr-plugin-rfc|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-rfc] and i've just created [master-ltr-plugin-rfc-cpoerschke-comments|https://github.com/bloomberg/lucene-solr/tree/master-ltr-plugin-rfc-cpoerschke-comments] branch off that. In (unrelated) SOLR-8621 we had an in-progress branch also and its usage and intentions emerged and were clarified over time, and so based on that perhaps it's helpful to suggest usage up-front here: * master-ltr-plugin-rfc branches off (Jan 29th) master * master-ltr-plugin-rfc-cpoerschke-comments branches off (Feb 24th) master-ltr-plugin-rfc * 'git merge' and 'git rebase' and 'git --force push' will be avoided * further commits to master-ltr-plugin-rfc* are anticipated * 'git cherry-pick' of changes from master to master-ltr-plugin-rfc* will be done where helpful (e.g. SOLR-8600 was cherry-picked from master to master-ltr-plugin-rfc-cpoerschke-comments) * cherry-picking between master-ltr-plugin-rfc* branches welcome and will be done where helpful * at some point in the future activity on master-ltr-plugin-rfc* branches will cease and if required a new (say) master-ltr-plugin-rfc-march branch off (Mar 1?th) master will be created * at the very end everything will be squashed and rebased onto latest master and then committed as a single commit Does that sound workable or too complicated? Alternatives, comments, etc. welcome as usual. (And to clarify, suggested usage here is specific for this SOLR-8542 ticket only, any general recommended usage type discussions would be for elsewhere.) > 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, > 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