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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SOLR-8542) Integrate Learning to Rank into Solr
Date Wed, 09 Mar 2016 17:41:42 GMT

    [ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15187489#comment-15187489
] 

ASF GitHub Bot commented on SOLR-8542:
--------------------------------------

Github user alessandrobenedetti commented on a diff in the pull request:

    https://github.com/apache/lucene-solr/pull/4#discussion_r55557481
  
    --- Diff: solr/contrib/ltr/src/java/org/apache/solr/ltr/ranking/ModelQuery.java ---
    @@ -0,0 +1,540 @@
    +package org.apache.solr.ltr.ranking;
    +
    +/*
    + * Licensed to the Apache Software Foundation (ASF) under one or more
    + * contributor license agreements.  See the NOTICE file distributed with
    + * this work for additional information regarding copyright ownership.
    + * The ASF licenses this file to You under the Apache License, Version 2.0
    + * (the "License"); you may not use this file except in compliance with
    + * the License.  You may obtain a copy of the License at
    + *
    + *     http://www.apache.org/licenses/LICENSE-2.0
    + *
    + * Unless required by applicable law or agreed to in writing, software
    + * distributed under the License is distributed on an "AS IS" BASIS,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +import java.io.IOException;
    +import java.util.ArrayList;
    +import java.util.Collection;
    +import java.util.HashMap;
    +import java.util.List;
    +import java.util.Map;
    +import java.util.Set;
    +
    +import org.apache.lucene.index.LeafReaderContext;
    +import org.apache.lucene.index.Term;
    +import org.apache.lucene.search.DisiPriorityQueue;
    +import org.apache.lucene.search.DisiWrapper;
    +import org.apache.lucene.search.DisjunctionDISIApproximation;
    +import org.apache.lucene.search.DocIdSetIterator;
    +import org.apache.lucene.search.Explanation;
    +import org.apache.lucene.search.IndexSearcher;
    +import org.apache.lucene.search.Query;
    +import org.apache.lucene.search.Scorer;
    +import org.apache.lucene.search.Weight;
    +import org.apache.lucene.search.Scorer.ChildScorer;
    +import org.apache.solr.ltr.feature.ModelMetadata;
    +import org.apache.solr.ltr.feature.norm.Normalizer;
    +import org.apache.solr.ltr.feature.norm.impl.IdentityNormalizer;
    +import org.apache.solr.ltr.log.FeatureLogger;
    +import org.apache.solr.request.SolrQueryRequest;
    +
    +/**
    + * The ranking query that is run, reranking results using the ModelMetadata
    + * algorithm
    + */
    +public class ModelQuery extends Query {
    +
    +  // contains a description of the model
    +  protected ModelMetadata meta;
    +  // feature logger to output the features.
    +  private FeatureLogger fl = null;
    +  // Map of external parameters, such as query intent, that can be used by
    +  // features
    +  protected Map<String,String> efi;
    +  // Original solr query used to fetch matching documents
    +  protected Query originalQuery;
    +  // Original solr request
    +  protected SolrQueryRequest request;
    +
    +  public ModelQuery(ModelMetadata meta) {
    +    this.meta = meta;
    +  }
    +
    +  public ModelMetadata getMetadata() {
    +    return meta;
    +  }
    +
    +  public void setFeatureLogger(FeatureLogger fl) {
    +    this.fl = fl;
    +  }
    +
    +  public FeatureLogger getFeatureLogger() {
    +    return this.fl;
    +  }
    +
    +  public Collection<Feature> getAllFeatures() {
    +    return meta.getAllFeatures();
    +  }
    +
    +  public void setOriginalQuery(Query mainQuery) {
    +    this.originalQuery = mainQuery;
    +  }
    +
    +  public void setExternalFeatureInfo(Map<String,String> externalFeatureInfo) {
    +    this.efi = externalFeatureInfo;
    +  }
    +
    +  public void setRequest(SolrQueryRequest request) {
    +    this.request = request;
    +  }
    +
    +  @Override
    +  public int hashCode() {
    +    final int prime = 31;
    +    int result = super.hashCode();
    +    result = prime * result + ((meta == null) ? 0 : meta.hashCode());
    +    result = prime * result
    +        + ((originalQuery == null) ? 0 : originalQuery.hashCode());
    +    result = prime * result + ((efi == null) ? 0 : originalQuery.hashCode());
    --- End diff --
    
    I think this is a typo.
    It should be :
    result = prime * result + ((efi == null) ? 0 : efi.hashCode());
    
    This is a small thing but actually currently make the system not usable when you experiment
different refi variable values. Basically the cache is always hit, even if your refi variables
change dynamically.
    Anyway is really a minimal fix :)


> 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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