Query topic detection for reformulation

In this paper, we show that most multiple term queries include more than one topic and users usually reformulate their queries by topics instead of terms. In order to provide empirical evidence on user's reformulation behavior and to help search engines better handle the query reformulation problem, we focus on detecting internal topics in the original query and analyzing users' reformulation to those topics. Particularly, we utilize the Interaction Information (II) to measure the degree of one sub-query being a topic based on the local search results. The experimental results on query log show that: most users reformulate query at the topical level; and our proposed II-based algorithm is a good method to detect topics from original queries. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: Query formulation General Terms Algorithms, Experimentation Keywords Query reformulation, Topic, Interaction Information

• Type: Conference
• Year: 2007
• Where: WWW
• Authors: Xuefeng He, Jun Yan, Jinwen Ma, Ning Liu, Zheng Chen
• Keywords: Internet Technology, Keywords Query Reformulation, Query Reformulation Problem, Users Reformulate Query, WWW 2007