ABSTRACT
Most commercial search engines have a query suggestion feature, which is designed to capture various possible search intents behind the user's original query. However, even though different search intents behind a given query may have been popular at different time periods in the past, existing query suggestion methods neither utilize nor present such information. In this study, we propose Time-aware Structured Query Suggestion (TaSQS) which clusters query suggestions along a timeline so that the user can narrow down his search from a temporal point of view. Moreover, when a suggested query is clicked, TaSQS presents web pages from query-URL bipartite graphs after ranking them according to the click counts within a particular time period. Our experiments using data from a commercial search engine log show that the time-aware clustering and the time-aware document ranking features of TaSQS are both effective.
- Z. Bar-Yossef and N. Kraus. Context-sensitive query auto-completion. In WWW, pages 107--116, 2011. Google ScholarDigital Library
- O. Chapelle, D. Metlzer, Y. Zhang, and P. Grinspan. Expected reciprocal rank for graded relevance. In CIKM, pages 621--630, 2009. Google ScholarDigital Library
- J. Guo, X. Cheng, G. Xu, and H. Shen. A structured approach to query recommendation with social annotation data. In CIKM, pages 619--628, 2010. Google ScholarDigital Library
- K. Järvelin and J. Kekäläinen. Cumulated gain-based evaluation of IR techniques. TOIS, 20(4):422--446, 2002. Google ScholarDigital Library
- M. P. Kato, T. Sakai, and K. Tanaka. Structured query suggestion for specialization and parallel movement: effect on search behaviors. In WWW, pages 389--398, 2012. Google ScholarDigital Library
- X. Li and W. Croft. Time-based language models. In CIKM, pages 469--475, 2003. Google ScholarDigital Library
- Q. Mei, D. Zhou, and K. Church. Query suggestion using hitting time. In CIKM, pages 469--478, 2008. Google ScholarDigital Library
- E. Sadikov, J. Madhavan, L. Wang, and A. Halevy. Clustering query refinements by user intent. In WWW, pages 841--850, 2010. Google ScholarDigital Library
- M. Shokouhi and K. Radinsky. Time-sensitive query auto-completion. In SIGIR, pages 601--610, 2012. Google ScholarDigital Library
Index Terms
- Time-aware structured query suggestion
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