Simrank++

Ioannis Antonellis, Hector Garcia Molina, Chi Chao Chang
2008 Proceedings of the VLDB Endowment  
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 [2] 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 versions of Simrank: one that exploits weights on
more » ... 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.
doi:10.14778/1453856.1453903 fatcat:pmn2lfdtnfdn3p3jy7xvnfcyi4