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From "Eks Dev (JIRA)" <j...@apache.org>
Subject [jira] Commented: (LUCENE-1532) File based spellcheck with doc frequencies supplied
Date Fri, 30 Jan 2009 20:54:59 GMT

    [ https://issues.apache.org/jira/browse/LUCENE-1532?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12669018#action_12669018
] 

Eks Dev commented on LUCENE-1532:
---------------------------------

bq. so it can suggest a very obscure word rather than a more common word which is equally
close to the misspelled word that was entered

in my experience freq information brings there a lot, but is not linear. It is not always
that word with higher frequency makes better suggestion. Common sense is that high frequency
words get often misspelled in different ways in normal corpus. Making following patterns:


HF(High Freiquency) Word against LF(Low Frequency) that is similar in edit distance sense
is much more likely typo/misspelling than HF vs HF case. 

Similar cases with HF vs LF
"the" against "hte"
"think" vs "tihnk"

Very similar, but HF vs HF 
"think" vs "thing"

some cases that jump out of these ideas are synonyms, alternative spellings and very common
mistakes. Very tricky to isolate just by using some distance measure and frequency. Her you
need context.
similar and HF vs HF
"thomas" vs "tomas" sometimes spelling mistake, sometimes different names...

depends what you are trying to achieve, if you expect mistakes in query you are good if you
assume HF suggestions are better, but if you go for high recall you need to cover cases where
query  term is correct  you have to dig into your corpus to find incorrect words (Query "think
about it" should find document containing "tihnk about it")

very challenging problem.... but cutting to the chase. The proposal is to make it possible
to define
 float Function(Edit distance, Query_Token_Freq, Corpus_Token_Freq) that returns some measure
that is higher  for more similar pairs considering edit distance and frequency (value that
gets used as condition for priority queue) . Default could just work as you described. (It
is maybe already possible, I  did not look at it). 

  



 


> File based spellcheck with doc frequencies supplied
> ---------------------------------------------------
>
>                 Key: LUCENE-1532
>                 URL: https://issues.apache.org/jira/browse/LUCENE-1532
>             Project: Lucene - Java
>          Issue Type: New Feature
>          Components: contrib/spellchecker
>            Reporter: David Bowen
>
> The file-based spellchecker treats all words in the dictionary as equally valid, so it
can suggest a very obscure word rather than a more common word which is equally close to the
misspelled word that was entered.  It would be very useful to have the option of supplying
an integer with each word which indicates its commonness.  I.e. the integer could be the document
frequency in some index or set of indexes.
> I've implemented a modification to the spellcheck API to support this by defining a DocFrequencyInfo
interface for obtaining the doc frequency of a word, and a class which implements the interface
by looking up the frequency in an index.  So Lucene users can provide alternative implementations
of DocFrequencyInfo.  I could submit this as a patch if there is interest.  Alternatively,
it might be better to just extend the spellcheck API to have a way to supply the frequencies
when you create a PlainTextDictionary, but that would mean storing the frequencies somewhere
when building the spellcheck index, and I'm not sure how best to do that.

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