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From "Elmar Pitschke (JIRA)" <j...@apache.org>
Subject [jira] Commented: (LUCENE-2749) Co-occurrence filter
Date Thu, 17 Mar 2011 06:54:29 GMT

    [ https://issues.apache.org/jira/browse/LUCENE-2749?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13007837#comment-13007837
] 

Elmar Pitschke commented on LUCENE-2749:
----------------------------------------

The first use case that comes into my mind is the filtering of possible names. One of the
request i always get is the automatic generation of tag-clouds with a consideration in the
search results. I think this would be one possibility to get names without the need to maintain
a word list.
Another thing of course would be to get some kind of semantic combination of words. So you
could get to more "natural" search experience. I think if a user search for two words and
these are quite near in a text it may be more useful than a lot of occurances of the two words
but with no combination.
Which use cases do you have in mind?

> Co-occurrence filter
> --------------------
>
>                 Key: LUCENE-2749
>                 URL: https://issues.apache.org/jira/browse/LUCENE-2749
>             Project: Lucene - Java
>          Issue Type: New Feature
>          Components: Analysis
>    Affects Versions: 3.1, 4.0
>            Reporter: Steven Rowe
>            Priority: Minor
>             Fix For: 4.0
>
>
> The co-occurrence filter to be developed here will output sets of tokens that co-occur
within a given window onto a token stream.  
> These token sets can be ordered either lexically (to allow order-independent matching/counting)
or positionally (e.g. sliding windows of positionally ordered co-occurring terms that include
all terms in the window are called n-grams or shingles). 
> The parameters to this filter will be: 
> * window size: this can be a fixed sequence length, sentence/paragraph context (these
will require sentence/paragraph segmentation, which is not in Lucene yet), or over the entire
token stream (full field width)
> * minimum number of co-occurring terms: >= 2
> * maximum number of co-occurring terms: <= window size
> * token set ordering (lexical or positional)
> One use case for co-occurring token sets is as candidates for collocations.

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