[jira] [Updated] (LUCENE-6954) More Like This Query Generation

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

     [ https://issues.apache.org/jira/browse/LUCENE-6954?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Alessandro Benedetti updated LUCENE-6954:
-----------------------------------------
    Attachment: LUCENE-6954.patch

First draft patch available, I had some problem in my environment to check the overall tests.
Will provide some check next year :)

> More Like This Query Generation 
> --------------------------------
>
>                 Key: LUCENE-6954
>                 URL: https://issues.apache.org/jira/browse/LUCENE-6954
>             Project: Lucene - Core
>          Issue Type: Improvement
>          Components: modules/other
>    Affects Versions: 5.4
>            Reporter: Alessandro Benedetti
>              Labels: morelikethis
>         Attachments: LUCENE-6954.patch
>
>
> Currently the query is generated : 
> org.apache.lucene.queries.mlt.MoreLikeThis#retrieveTerms(int)
> 1) we extract the terms from the interesting fields, adding them to a map :
> Map<String, Int> termFreqMap = new HashMap<>();
> ( we lose the relation field-> term, we don't know anymore where the term was coming ! )
> org.apache.lucene.queries.mlt.MoreLikeThis#createQueue
> 2) we build the queue that will contain the query terms, at this point we connect again there terms to some field, but :
> ...
> // go through all the fields and find the largest document frequency
> String topField = fieldNames[0];
> int docFreq = 0;
> for (String fieldName : fieldNames) {
>   int freq = ir.docFreq(new Term(fieldName, word));
>   topField = (freq > docFreq) ? fieldName : topField;
>   docFreq = (freq > docFreq) ? freq : docFreq;
> }
> ...
> We identify the topField as the field with the highest document frequency for the term t .
> Then we build the termQuery :
> queue.add(new ScoreTerm(word, topField, score, idf, docFreq, tf));
> In this way we lose a lot of precision.
> Not sure why we do that.
> I would prefer to keep the relation between terms and fields.
> The MLT query can improve a lot the quality.
> If i run the MLT on 2 fields : weSell and weDontSell for example.
> It is likely I want to find documents with similar terms in the weSell and similar terms in the weDontSell, without mixing up the things and loosing the semantic of the terms.



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