Simrank++: Query rewriting through link analysis of the click graph
Loading...
Date
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Description
We focus on the problem of query rewriting for sponsored search. We base rewrites on a historical click graph that records the ads that have been clicked on in response to past user queries. Given a query q, we first consider Simrank as a way to identify queries similar to q, i.e., queries whose ads a user may be interested in. We argue that Simrank fails to properly identify query similarities in our application, and we present two enhanced version of Simrank: one that exploits weights on click graph edges and another that exploits ``evidence.'' We experimentally evaluate our new schemes against Simrank, using actual click graphs and queries form Yahoo!, and using a variety of metrics. Our results show that the enhanced methods can yield more and better query rewrites.
Available via http://dbpubs.stanford.edu/pub/2007-32
Available via http://dbpubs.stanford.edu/pub/2007-32