Poster Title:

Query Topic Detection for Reformulation

Authors:

• Xuefeng He (Peking University)
• Jun Yan (Microsoft Research Asia)
• Jinwen Ma (Peking university)
• Ning Liu (Microsoft Research Aisa)
• Zheng Chen (Microsoft Research Asia)

Abstract:

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 in this paper. We utilize the Interaction Information (II) to measure the degree of one subquery 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.