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From "Allison, Timothy B." <>
Subject RE: Partial word match using n-grams
Date Fri, 19 Jul 2013 11:58:06 GMT
Got it...almost.  

Y. You're right. FuzzyQuery is not at all what you want.

Don't know if your data is actually as simple as this example.  Do you need to tokenize on
whitespace?   Would it make sense to replace spaces in the query with underscores and then
trigramify the whole query as if it were a single term?  

From: Becker, Thomas []
Sent: Thursday, July 18, 2013 8:59 PM
Subject: RE: Partial word match using n-grams

Thanks for the reply Tim.  I really should have been clearer.  Let's say I have an object
named "quota_tommy_1234".  I'd like to match that object with any 3 character (or more) substring
of that name.  So for example:


Further, at search time I'm splitting input on whitespace before tokenizing into PhraseQueries
and then ANDing them together.  So using the example above I also want the following queries
to match:

quo tom
quo 234
quota to <- this is the problem because there are no trigrams of "to"

That said, in response to your points:

1)  Not sure FuzzyQuery is what I need; I'm not trying to match via misspellings, which is
the main function of FuzzyQuery is it not?

2) The original names are all going to be > 3 characters, so there are no 1 or 2 letter
terms at indexing time.  So generating the bigram "to" at search time will never match anything,
unless I switch to bigrams at indexing time also, which is what I'm asking about.

3)  Again the names are all > 3 characters so I don't need to pad at indexing time.

4) Hopefully my explanation above clarifies.

I should point out that I'm a Lucene novice and am not at all sure that what I'm doing is
optimal.  But I have been impressed with how easy it is to get something working very quickly!

From: Allison, Timothy B. []
Sent: Thursday, July 18, 2013 7:49 PM
Subject: RE: Partial word match using n-grams

  I'm sure that I don't fully understand your use case and your data.  Some thoughts:

1) I assume that fuzzy term search (edit distance <= 2) isn't meeting your needs or else
you wouldn't have gone the ngram route.  If fuzzy term search + phrase/proximity search would
meet your needs, see if ComplexPhraseQueryParser would work (although it looks like you're
already building your own queries).

2) Would it make sense to modify NGramFilter so that it outputs a bigram for a two letter
term and a unigram for a one letter term?  Might be messy...and "ab" in this scenario would
never match "abc"

3) Would it make sense to pad your terms behind the scenes with "##"...this would add bloat,
but not nearly as much as variable gram sizes with 1<= n <=3

ab -> ##ab## yields trigrams ##a, #ab, ab#, b##

4) How partial and what types of partial do you need?  This is related to 1).  If minimum
edit distance is sufficient; use it, especially with the blazing fast automaton (thank you,
Robert Muir). If you have a smallish dataset you might consider allowing leading wildcards
so that you could easily find all words, for example, containing abc with *abc*.  If your
dataset is larger, you might consider something like ReversedWildcardFilterFactory (Solr)
to speed this type of matching.

I look forward to other opinions from the list.

-----Original Message-----
From: Becker, Thomas []
Sent: Thursday, July 18, 2013 3:55 PM
Subject: Partial word match using n-grams

One of our main use-cases for search is to find objects based on partial name matches.  I've
implemented this using n-grams and it works pretty well.  However we're currently using trigrams
and that causes an interesting problem when searching for things like "abc ab" since we first
split on whitespace and then construct PhraseQuerys containing each trigram yielded by the
"word".  Obviously we cannot get a trigram out of "ab".  So our choices would seem to be either
discard this part of the search term which seems unwise, or to reduce the minimum n-gram size.
 But I'm slightly concerned about the resulting bloat in both the of number of Terms stored
in the index as well as contained in queries.  Is this something I should be concerned about?
 It just "feels" like a query for the word "abcdef" shouldn't require a PhraseQuery of 15
terms (assuming n-grams 1,3).  Is this the best way to do partial word matches?  Thanks in


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