hum, quote and question disappear.
Le 2 mars 08 à 13:32, Mathieu Lecarme (JIRA) a écrit :
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Mathieu Lecarme commented on LUCENE-1190:
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>> For example, I don't know what you mean by "Some Lucene features
need a list of referring word". Do you mean "a list of associated
words"?
With a FuzzyQuery, for example, you iterate over Term in index, and
looking for the nearest one. PrefixQuery or regular expression work in
a similar way.
If you say, fuzzy querying will never gives a word with different size
of 1 (size+1 or size -1), you can restrict the list of candidates, and
ngram index can help you more.
Some token filter destroy the word. Stemmer for example. If you wont
to search wide, stemmer can help you, but can't use PrefixQuery with
stemmed word. So, you can stemme word in a lexicon and use it as a
synonym. You index "dog" and look for "doggy", "dogs" and "dog".
Lexicon can use static list of word, from hunspell index or wikipedia
parsing, or words extracted from your index.
>> Each meta is a Field.... what do you mean by that? Could you
please give an example?
for the word "Lucene" :
word:lucene
pop:42
anagram.anagram:celnu
aphone.start:LS
aphone.gram:LS
aphone.gram:SN
aphone.end:SN
aphone.size:3
aphone.phonem:LSN
ngram.start:lu
ngram.gram:lu
ngram.gram:uc
ngram.gram:ce
ngram.gram:en
ngram.gram:ne
ngram.end:ne
ngram.size:6
stemmer.stem:lucen
>> Hm, not sure I know what you mean. Are you saying that once you
create a sufficiently large lexicon/dictionary/index, the number of
new terms starts decreasing? (Heap's Law? http://en.wikipedia.org/wiki/Heaps'_law
)
Yes.
a lexicon object for merging spellchecker and synonyms from stemming
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Key: LUCENE-1190
URL: https://issues.apache.org/jira/browse/LUCENE-1190
Project: Lucene - Java
Issue Type: New Feature
Components: contrib/*, Search
Affects Versions: 2.3
Reporter: Mathieu Lecarme
Attachments: aphone+lexicon.patch, aphone+lexicon.patch
Some Lucene features need a list of referring word. Spellchecking
is the basic example, but synonyms is an other use. Other tools can
be used smoothlier with a list of words, without disturbing the
main index : stemming and other simplification of word (anagram,
phonetic ...).
For that, I suggest a Lexicon object, wich contains words (Term +
frequency), wich can be built from Lucene Directory, or plain text
files.
Classical TokenFilter can be used with Lexicon (LowerCaseFilter and
ISOLatin1AccentFilter should be the most useful).
Lexicon uses a Lucene Directory, each Word is a Document, each meta
is a Field (word, ngram, phonetic, fields, anagram, size ...).
Above a minimum size, number of differents words used in an index
can be considered as stable. So, a standard Lexicon (built from
wikipedia by example) can be used.
A similarTokenFilter is provided.
A spellchecker will come soon.
A fuzzySearch implementation, a neutral synonym TokenFilter can be
done.
Unused words can be remove on demand (lazy delete?)
Any criticism or suggestions?
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