Time-Dependent Semantic Similarity Measure of Queries Using Historical Click-Through Data
Conference Proceeding Article
It has become a promising direction to measure similarity of Web search queries by mining the increasing amount of click-through 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 semantics from the click-through data effectively. Experimental results on a large set of click-through data acquired from a commercial search engine show that our time-dependent query similarity model is more accurate than the existing approaches. Moreover, we observe that our time-dependent query similarity model can, to some extent, reflect real-world semantics such as real-world events that are happening over time.
click-through data, semantic similarity measure, marginalizedkernel, event detection, evolution pattern
Computer Sciences | Databases and Information Systems
Data Management and Analytics
Proceedings of the 15th International Conference on World Wide Web: Edinburgh, Scotland, May 23-26, 2006
City or Country
ZHAO, Qiankun; HOI, Steven C. H.; LIU, Tie-Yan; BHOWMICK, Sourav S.; LYU, Michael R.; and MA, Wei-Ying.
Time-Dependent Semantic Similarity Measure of Queries Using Historical Click-Through Data. (2006). Proceedings of the 15th International Conference on World Wide Web: Edinburgh, Scotland, May 23-26, 2006. 543-552. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2391