The current suggesters are all based on a finite space of possible
suggestions, i.e. the ones they were built on, so they can only
suggest a full suggestion from that space.
This means if the current query goes outside of that space then no
suggestions will be found.
The goal of FreeTextSuggester is to address this, by giving
predictions based on an ngram language model, i.e. using the last few
tokens from the user's query to predict likely following token.
I got the idea from this blog post about Google's suggest:
This is very much still a work in progress, but it seems to be
working. I've tested it on the AOL query logs, using an interactive
tool from luceneutil to show the suggestions, and it seems to work well.
It's fun to use that tool to explore the word associations...
I don't think this suggester would be used standalone; rather, I think
it'd be a fallback for times when the primary suggester fails to find
anything. You can see this behavior on google.com, if you type "the
fast and the ", you see entire queries being suggested, but then if
the next word you type is "burning" then suddenly you see the
suggestions are only based on the last word, not the entire query.
It uses ShingleFilter under-the-hood to generate the token ngrams;
LUCENE-5180 is in it will be able to properly handle a user query
that ends with stop-words (e.g. "wizard of "), and then stores the
ngrams in an FST.
|Transition||Time In Source Status||Execution Times||Last Executer||Last Execution Date|
|17d 1h 54m||1||Michael McCandless||02/Oct/13 16:31|
|Status||Open [ 1 ]||Resolved [ 5 ]|
|Resolution||Fixed [ 1 ]|