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https://issues.apache.org/jira/browse/LUCENE-3714?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dawid Weiss updated LUCENE-3714:
--------------------------------
Attachment: out.png
An problematic example where root arcs, when traversed min-to-max collect
outputs, but every outgoing arc only collects a single better suggestion (and
should skip possibly lots of other suggestions). This is created by the
following input:
aa|N
ab|1
ba|N
bb|2
ca|N
cb|3
..
collecting the K-th suggestion with the smallest score will require scanning
pessimistically all of the arcs. Note that you can put arbitrarily large
subtrees on _a|N nodes like:
aaa|N
aab|N
aac|N
etc.
> 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, 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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