Simrank++: Query Rewriting through Link Analysis of the Click Graph

被引：125

作者：

Antonellis, Ioannis ^{[1
]}

Molina, Hector Garcia ^{[1
]}

Chang, Chi Chao ^{[2
]}

机构：

[1] Stanford Univ, Comp Sci Dept, Stanford, CA 94305 USA

[2] Yahoo Inc, Sunnyvale, CA 94089 USA

来源：

PROCEEDINGS OF THE VLDB ENDOWMENT | 2008年 / 1卷 / 01期

关键词：

sponsored search; link analysis; similarity metric; click graph;

D O I：

10.14778/1453856.1453903

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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 Sim-rank [ 7] as a way to identify queries similar to q, i.e., queries whose ads a user may be interested in. We argue that Sim-rank fails to properly identify query similarities in our application, and we present two enhanced versions of Sim-rank: 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 from Yahoo!, and using a variety of metrics. Our results show that the enhanced methods can yield more and better query rewrites.

引用

页码：408 / 421

页数：14