Ranking with Query-Dependent Loss for Web Search

Queries describe the users' search intent and therefore they play an essential role in the context of ranking for information retrieval and Web search. However, most of existing approaches for ranking do not explicitly take into consideration the fact that queries vary significantly along several dimensions and entail different treatments regarding the ranking models. In this paper, we propose to incorporate query difference into ranking by introducing querydependent loss functions. In the context of Web search, query difference is usually represented as different query categories; and, queries are usually classified according to search intent such as navigational, informational and transactional queries. Based on the observation that such kind of query categorization has high correlation with the user's different expectation on the result accuracy on different rank positions, we develop position-sensitive query-dependent loss functions exploring such kind of query categoriz...

• Type: Conference
• Year: 2010
• Where: WSDM
• Authors: Jiang Bian, Tie-Yan Liu, Tao Qin, Hongyuan Zha
• Keywords: Data Mining, Particular Ranking Algorithms, Pre-defined Query Categorization, Ranking Functions, WSDM 2010