Hi, I think there is nothing available except FTS.
Doing a full table scan and computing for each string the (Levenstein) distance
to the query object is too time consuming. So what I would like to see is the 
implementation
of a generic metric index which needs as one parameter a metric distance 
function. Based on such a 
distance function you could then do similarity search on any objects , e.g. 
images, strings, etc.
One possible index would be the M-tree (which you can also organize relational 
as it was done
with the R*-tree). The idea is that you have a hierarchical index and each node 
is represented by
a database  object o and a covering radius r reflecting the maximal distance of 
all objects in that subtree to
the object o. If you do a range query now, you compute the distance of your 
query object to the
 object o. If this distance minus the coverage radius r is bigger than your 
query range
you can prune that subtree.
You can either implement such a similarity module as an own extension similar 
toFTS or the Spatial module,
or integrate it into FTS and use it only for strings.
Personally, I need the second solution because I'd like to do full and fuzzy 
text search.
Are there any plans to implement something like this, if yes, I would like to 
take part in such a
development. 
.
Best Martin
 
 


----- Ursprüngliche Mail ----
Von: Alberto Simões <[EMAIL PROTECTED]>
An: General Discussion of SQLite Database <sqlite-users@sqlite.org>
Gesendet: Donnerstag, den 3. Juli 2008, 21:52:05 Uhr
Betreff: [sqlite] Fuzzy Matching

Hello

Although I am quite certain that the answer is that SQLite does not
provide any mechanism to help me on this, it doesn't hurt to ask. Who
know if anybody have any suggestion.

Basically, I am using SQLite for a dictionary, and I want to let the
user do fuzzy searches. OK, some simple Levenshtein distance of one or
two would do the trick, probably.

I imagine that SQLite (given the lite), does not provide any kind of
nearmisses search.
But probably, somebody here did anything similar in any language?

Cheers
Alberto
-- 
Alberto Simões
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