For this you probably want to use ngrams. Wether or not this is something that fits in your current index is hard to say. My guess is that you want to create a new index with one document per unique phrase. You might also want to try to load this index in an InstantiatedIndex, that could speed things up quite a bit if the corpus is not too large.

If your suggestion text corpus is really large and you only want forward-only suggestions then you might want to consider a trie- pattern solution instead. These can be rather resource efficient, even when loaded to memory.

If you have a lot of user load on your search eninge then it might be interesting to use old user queries as the base of your suggestions and perhaps boost a bit on trends, i.e. the more people search for something the more it get boosted in the suggestions list.


     karl

8 apr 2009 kl. 15.26 skrev Matt Schraeder:

I want to add a suggestive search similar to google's to autocomplete
search phrases as the user types. It doesn't have to be very elaborate
and for the most part will just involve searching single fields.  How
can I perform a search  to be able to fill in autocomplete text?

For instance, if I start typing "Harr" it should bring up "Harry
Potter" "Harry Houdini" and "Harry S. Truman"

I have tried doing search queries for "Harr*" but it's still doing
term-based searching rather than searching a full field.  To make a
field both searchable as the full field as well as tokenized, would I
have to duplicate the field and make one a keyword field? Is there a
more convenient way to do this? I have also considered making a second
index for suggestive search, which would only have the fields that I
want to enable suggestive search on, but this seems like it would be
unneccesary duplication of data as well, though it would probably make
suggestive search faster due to a smaller index.

Ideally it would also be nice to be able to rank these terms based on
the number of times they have been searched for so that the results are tailored more to our users rather than simply just the score that Lucene
chooses.


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