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https://issues.apache.org/jira/browse/SOLR-11662?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16276157#comment-16276157
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ASF GitHub Bot commented on SOLR-11662:
---------------------------------------

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

    https://github.com/apache/lucene-solr/pull/275#discussion_r154540898
  
    --- Diff: 
solr/solr-ref-guide/src/field-type-definitions-and-properties.adoc ---
    @@ -87,6 +87,13 @@ For multivalued fields, specifies a distance between 
multiple values, which prev
     
     `autoGeneratePhraseQueries`:: For text fields. If `true`, Solr 
automatically generates phrase queries for adjacent terms. If `false`, terms 
must be enclosed in double-quotes to be treated as phrases.
     
    +`synonymQueryStyle`:: 
    +Query used to combine scores of overlapping query terms (ie synonyms). 
Consider a search for "blue tee" with query-time synonyms `tshirt,tee`.
    ++
    +Use `as_same_term` (default) to blend terms, ie `SynonymQuery(tshirt,tee)` 
where each term will be treated as equally important. Use `pick_best` to select 
the most significant synonym when scoring `Dismax(tee,tshirt)`. Use 
`as_distinct_terms` to bias scoring towards the most significant synonym 
`(pants OR slacks)`.
    ++
    +`as_same_term` is appropriatte when terms are true synonyms (television, 
tv). `pick_best` and `as_distinct_terms` are appropriatte when synonyms are 
expanding to hyponyms (q=jeans w/ jeans=>jeans,pants) and you want exact to 
come before parent and sibling concepts. See this 
http://opensourceconnections.com/blog/2017/11/21/solr-synonyms-mea-culpa/[blog 
article].
    --- End diff --
    
    Thanks @ctargett, this is one of those words I consistently misspell. 
Github spellchecking failed me, so I brought it down and double checked/fixed 
the spelling.


> Make overlapping query term scoring configurable per field type
> ---------------------------------------------------------------
>
>                 Key: SOLR-11662
>                 URL: https://issues.apache.org/jira/browse/SOLR-11662
>             Project: Solr
>          Issue Type: Improvement
>      Security Level: Public(Default Security Level. Issues are Public) 
>            Reporter: Doug Turnbull
>             Fix For: 7.2, master (8.0)
>
>
> This patch customizes the query-time behavior when query terms overlap 
> positions. Right now the only option is SynonymQuery. This is a fantastic 
> default & improvement on past versions. However, there are use cases where 
> terms overlap positions but don't carry exact synonymy relationships. Often 
> synonyms are actually used to model hypernym/hyponym relationships using 
> synonyms (or other analyzers). So the individual term scores matter, with 
> terms with higher specificity (hyponym) scoring higher than terms with lower 
> specificity (hypernym).
> This patch adds the fieldType setting scoreOverlaps, as in:
> {code:java}
>   <fieldType name="text_general"  scoreOverlaps="pick_best"  
> class="solr.TextField" positionIncrementGap="100" multiValued="true">
> {code}
> Valid values for scoreOverlaps are:
> *as_one_term*
> Default, most synonym use cases. Uses SynonymQuery
> Treats all terms as if they're exactly equivalent, with document frequency 
> from underlying terms blended 
> *pick_best*
> For a given document, score using the best scoring synonym (ie dismax over 
> generated terms). 
> Useful when synonyms not exactly equilevant. Instead they are used to model 
> hypernym/hyponym relationships. Such as expanding to synonyms of where terms 
> scores will reflect that quality
> IE this query time expansion
> tabby => tabby, cat, animal
> Searching "text", generates the dismax (text:tabby | text:cat | text:animal)
> *as_distinct_terms*
> (The pre 6.0 behavior.)
> Compromise between pick_best and as_oneSterm
> Appropriate when synonyms reflect a hypernym/hyponym relationship, but lets 
> scores stack, so documents with more tabby, cat, or animal the better w/ a 
> bias towards the term with highest specificity
> Terms are turned into a boolean OR query, with documen frequencies not blended
> IE this query time expansion
> tabby => tabby, cat, animal
> Searching "text", generates the boolean query (text:tabby  text:cat 
> text:animal)



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