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https://issues.apache.org/jira/browse/SOLR-651?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12641814#action_12641814
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Grant Ingersoll commented on SOLR-651:
--------------------------------------
{quote}
The assumption is if someone has asked for TF-IDF representation, one would not
expect the entire document to be back. So if the request is
qt=trvh&tf.tv=true&tv=true or tf=true one would expect only to get the
termvectors component.
{quote}
OK, I think I understand. You're suggesting that if one only wants one
component (i.e. TF), that we could flatten the structure a bit such that
instead of:
{code}
<lst name="display">
<int name="freq">2</int>
</lst>
{code}
we just do:
{code}
<int name="display">2</int>
{code}
The former is slightly more verbose, but then it only requires people to have
one approach to handling the various options, whereas the latter approach,
while more compact, requires people to have two ways of handling the output.
Is my understanding correct?
> 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,
> 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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