[
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&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: 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
> ./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
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