Time-dependent semantic similarity measure of queries using historical click-through data

It has become a promising direction to measure similarity of Web search queries by mining the increasing amount of clickthrough data logged by Web search engines, which record the interactions between users and the search engines. Most existing approaches employ the click-through data for similarity measure of queries with little consideration of the temporal factor, while the click-through data is often dynamic and contains rich temporal information. In this paper we present a new framework of time-dependent query semantic similarity model on exploiting the temporal characteristics of historical click-through data. The intuition is that more accurate semantic similarity values between queries can be obtained by taking into account the timestamps of the log data. With a set of user-defined calendar schema and calendar patterns, our time-dependent query similarity model is constructed using the marginalized kernel technique, which can exploit both explicit similarity and implicit seman...

• Type: Conference
• Year: 2006
• Where: WWW
• Authors: Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Sourav S. Bhowmick, Michael R. Lyu, Wei-Ying Ma
• Keywords: Internet Technology, Query Semantic Similarity, Query Similarity Model, Time-dependent Query Similarity, WWW 2006