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https://issues.apache.org/jira/browse/SOLR-651?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12641769#action_12641769
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Vaijanath N. Rao commented on SOLR-651:
---------------------------------------
Hi Grant,
I have applied the patch and to start with it is really good. I just have few
suggestions.
a) if one set qt=tvrh tv=true does not make sense as the user is anyway
requesting term vectors.
b) Repeating uniqueKeyFieldName for every record does not add any value.
c) Ideally what I would have liked is something below.
<response>
<lst name="termVectors">
<lst name="firstdoc">
<str name="term1">term1tf-idf</str>
<str name="term2">term1tf-idf</str>
....
</lst>
<lst name="seconddoc">
<str name="term1">term1tf-idf</str>
...
</lst>
....
</lst>
</response>
Having said all this, the above patch helps us a lot in terms of using solr for
document clustering.
--Thanks and Regards
Vaijanath
> A SearchComponent for fetching TF-IDF values
> --------------------------------------------
>
> Key: SOLR-651
> URL: https://issues.apache.org/jira/browse/SOLR-651
> Project: Solr
> Issue Type: New Feature
> Affects Versions: 1.3
> Reporter: Noble Paul
> Assignee: Grant Ingersoll
> Priority: Minor
> Fix For: 1.4
>
> Attachments: SOLR-651.patch, SOLR-651.patch, SOLR-651.patch
>
>
> A SearchComponent that can return TF-IDF vector for any given document in the
> SOLR index
> Query : A Document Number / a query identifying a Document
> Response : A Map of term vs.TF-IDF value of every term in the Selected
> Document
> Why ?
> Most of the Machine Learning Algorithms work on TFIDF representation of
> documents, hence adding a Request Handler proving the TFIDF representation
> will pave the way for incorporating Learning Paradigms to SOLR framework.
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