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From "Christine Poerschke (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SOLR-8542) Integrate Learning to Rank into Solr
Date Wed, 24 Feb 2016 14:39:18 GMT

    [ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15163098#comment-15163098
] 

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



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