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From Matthew Runo <mr...@zappos.com>
Subject Optimizing & Improving results based on user feedback
Date Tue, 27 Jan 2009 21:06:14 GMT
Hello folks!

We've been thinking about ways to improve organic search results for a  
while (really, who hasn't?) and I'd like to get some ideas on ways to  
implement a feedback system that uses user behavior as input.  
Basically, it'd work on the premise that what the user actually  
clicked on is probably a really good match for their search, and  
should be boosted up in the results for that search.

For example, if I search for "rain boots", and really love the 10th  
result down (and show it by clicking on it), then we'd like to capture  
this and use the data to boost up that result //for that search//.  
We've thought about using index time boosts for the documents, but  
that'd boost it regardless of the search terms, which isn't what we  
want. We've thought about using the Elevator handler, but we don't  
really want to force a product to the top - we'd prefer it slowly  
rises over time as more and more people click it from the same search  
terms. Another way might be to stuff the keyword into the document,  
the more times it's in the document the higher it'd score - but  
there's gotta be a better way than that.

Obviously this can't be done 100% in solr - but if anyone had some  
clever ideas about how this might be possible it'd be interesting to  
hear them.

Thanks for your time!

Matthew Runo
Software Engineer, Zappos.com
mruno@zappos.com - 702-943-7833


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