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https://issues.apache.org/jira/browse/LUCENE-1320?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12629763#action_12629763
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Karl Wettin commented on LUCENE-1320:
-------------------------------------
It really is quite a bit of work to downgrade this to 1.4, lots of generics but
it also depends on enum.
So if you don't want 1.5 in contrib/analyzers I vote for simply removing it
from trunk now and reintroducing it in the 3.1-dev trunk.
karl
> ShingleMatrixFilter, a three dimensional permutating shingle filter
> -------------------------------------------------------------------
>
> Key: LUCENE-1320
> URL: https://issues.apache.org/jira/browse/LUCENE-1320
> Project: Lucene - Java
> Issue Type: New Feature
> Components: contrib/analyzers
> Affects Versions: 2.3.2
> Reporter: Karl Wettin
> Assignee: Karl Wettin
> Priority: Blocker
> Fix For: 2.4
>
> Attachments: LUCENE-1320.txt, LUCENE-1320.txt, LUCENE-1320.txt
>
>
> Backed by a column focused matrix that creates all permutations of shingle
> tokens in three dimensions. I.e. it handles multi token synonyms.
> Could for instance in some cases be used to replaces 0-slop phrase queries
> with something speedier.
> {code:java}
> Token[][][]{
> {{hello}, {greetings, and, salutations}},
> {{world}, {earth}, {tellus}}
> }
> {code}
> passes the following test with 2-3 grams:
> {code:java}
> assertNext(ts, "hello_world");
> assertNext(ts, "greetings_and");
> assertNext(ts, "greetings_and_salutations");
> assertNext(ts, "and_salutations");
> assertNext(ts, "and_salutations_world");
> assertNext(ts, "salutations_world");
> assertNext(ts, "hello_earth");
> assertNext(ts, "and_salutations_earth");
> assertNext(ts, "salutations_earth");
> assertNext(ts, "hello_tellus");
> assertNext(ts, "and_salutations_tellus");
> assertNext(ts, "salutations_tellus");
> {code}
> Contains more and less complex tests that demonstrate offsets, posincr,
> payload boosts calculation and construction of a matrix from a token stream.
> The matrix attempts to hog as little memory as possible by seeking no more
> than maximumShingleSize columns forward in the stream and clearing up unused
> resources (columns and unique token sets). Can still be optimized quite a bit
> though.
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