Hi Jens, thanks for the answer. (Because of time constraints) I solved the problem in a different way, i.e. providing each model a client_id method and then summing up the individual fuzzy search results for each attribute.
I guess this is neither legant nor performant and I'm not happy with the resulting scores. But we can live with it for now. The main issues we have is the well known locking problem and the scores. The scores leave us with the problem that - while the order seems to be correct - we don't know where to cut the line to display results and what a relevant match is. For a dozen attributes I've seen scores from 0.something to 9.something, with a result close below 9 not even looling similar while just above 9 seems to be a "99 percent" match. If someone would tell me - in case this is possible at all - how to normalize the scores I'd be very happy. Another thing which I didn't understand yet is what actually happens if I do a multi token fuzzy search; currently I'm splitting the string up in multiple tokens and build one query "attribute:token1~ AND attribute:token2~ AND ...". Maybe not really what I should do to get correct scores. Anyways, thanks for your work and for answering my post. -- Posted via http://www.ruby-forum.com/. _______________________________________________ Ferret-talk mailing list [email protected] http://rubyforge.org/mailman/listinfo/ferret-talk
