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https://issues.apache.org/jira/browse/LUCENE-3714?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13190778#comment-13190778
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Dawid Weiss commented on LUCENE-3714:
-------------------------------------
You're correct -- I should be comparing full paths so far, not the current
label. Otherwise I see we're pretty much the same. I like the lower bound
cutoff condition. I vaguely understand the NO_OUTPUT optimization. :)
I like it, this indeed is a nice improvement - if somebody wants exact scores,
they can have them.
> 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, 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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