[jira] [Commented] (SOLR-8542) Integrate Learning to Rank into Solr

["adeppa (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SOLR-8542?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15724818#comment-15724818 ] 

adeppa commented on SOLR-8542:
------------------------------

Hi Team,

I am working on LTR master branch with solr 6.3, when i try to integrate code in eclipse showing to me compile time errors in couple of class i.e FieldLengthFeatureWeight,LTRScoringQuery ,After adding the unimplemented  methods to couple of class i.e FieldValueFeatureWeight,SolrFeatureWeight,ValueFeatureWeight ,

In the LTRScoringQuery class showing error on  
@Override
  public ModelWeight createWeight(IndexSearcher searcher, boolean needsScores, float boost)
      throws IOException 

Note :if i remove @Override  error is went off ,is it any impact 


and FieldLengthFeatureWeight class showing error on
public FieldLengthFeatureScorer(FeatureWeight weight,
          NumericDocValues norms) throws IOException {
        super(weight, norms);

Note : Here super (weight,norms ) method showing error 
and 
 @Override
      public float score() throws IOException {

        final long l = norms.longValue();
Note : norms.longValue(); statement is showing error 
please help me for the above error resolution  

Thanks
Adeppa


> 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-unsubscribe@lucene.apache.org
For additional commands, e-mail: dev-help@lucene.apache.org