Identifying vertical search intention of query through social tagging propagation

Authors:
Ning Liu;Jun Yan;Weiguo Fan;Qiang Yang;Zheng Chen
Affiliations:
Microsoft Research Asia, beijing, China;Microsoft Research Asia, beijing, China;Virginia Polytechnic Institute and State University, Blacksburg, USA;Hong Kong University of Science and Technology, Hong Kong, China;Microsoft Research Asia, beijing, China
Venue:
Proceedings of the 18th international conference on World wide web
Year:
2009

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Abstract

A pressing task during the unification process is to identify a user's vertical search intention based on the user's query. In this paper, we propose a novel method to propagate social annotation, which includes user-supplied tag data, to both queries and VSEs for semantically bridging them. Our proposed algorithm consists of three key steps: query annotation, vertical annotation and query intention identification. Our algorithm, referred to as TagQV, verifies that the social tagging can be propagated to represent Web objects such as queries and VSEs besides Web pages. Experiments on real Web search queries demonstrate the effectiveness of TagQV in query intention identification.