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https://issues.apache.org/jira/browse/LUCENE-3714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13193845#comment-13193845
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Michael McCandless commented on LUCENE-3714:
--------------------------------------------
Sorry, I'm not proposing we commit pre-quantizing the scores... I'm
just saying we'd learn more from the perf test that way. Ie, is WFST
slower because 1) it's doing precise scores, or 2) the topN algo is
slowish.
> add suggester that uses shortest path/wFST instead of buckets
> -------------------------------------------------------------
>
> Key: LUCENE-3714
> URL: https://issues.apache.org/jira/browse/LUCENE-3714
> Project: Lucene - Java
> Issue Type: New Feature
> Components: modules/spellchecker
> Reporter: Robert Muir
> Attachments: LUCENE-3714.patch, LUCENE-3714.patch, LUCENE-3714.patch,
> TestMe.java, out.png
>
>
> Currently the FST suggester (really an FSA) quantizes weights into buckets
> (e.g. single byte) and puts them in front of the word.
> This makes it fast, but you lose granularity in your suggestions.
> Lately the question was raised, if you build lucene's FST with
> positiveintoutputs, does it behave the same as a tropical semiring wFST?
> In other words, after completing the word, we instead traverse min(output) at
> each node to find the 'shortest path' to the
> best suggestion (with the highest score).
> This means we wouldnt need to quantize weights at all and it might make some
> operations (e.g. adding fuzzy matching etc) a lot easier.
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