Comparing client and server dwell time estimates for click-level satisfaction prediction

SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2014, Pages 895-898

  Kim, Youngho ^a   Hassan, Ahmed ^b   White, Ryen W ^b   Zitouni, Imed ^b  

^a UNIVERSITY OF MASSACHUSETTS   (United States)

^b MICROSOFT   (United States)

Author keywords

Click satisfaction; Dwell time analysis

Indexed keywords

INFORMATION RETRIEVAL; SEARCH ENGINES;

CLICK SATISFACTION; CLIENT SIDES; DWELL TIME; LANDING PAGES; PREDICTION PERFORMANCE; SEARCH ENGINE RESULTS; SEARCH PROCESS; TOOLBARS;

FORECASTING;

EID: 84904572510     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2600428.2609468     Document Type: Conference Paper

References (17)

1. Bilenko, M. and White, R. W. (2008). Mining the search trails of surfing crowds: Identifying relevant websites from user activity. Proc. WWW, 51-60.
2. Claypool, M., Le, Phong, Waseda, M., and Brown, D. (2001). Implicit interest indicators. Proc. IUI, 33-40.
3. Cronen-Townsend, S., Zhou, Y., and Croft, W.B. (2002). Predicting query performance. Proc. SIGIR, 299306.
4. Downey, D., Dumais, S.T., and Horvitz, E. (2007). Models of searching and browsing: Languages, studies, and applications. Proc. IJCAI, 27402747.
5. Fox, S., Karnawat, K., Mydland, M., Dumais, S., and White, T. (2005). Evaluating implicit measures to improve web search. ACM TOIS, 23(2): 147168.
6. Friedman, J.H. (2001). Greedy function approximation: a gradient boosting machine. The Annals of Statistics, 29(5): 11891232.
7. Hassan, A., Jones, R., and Klinkner, K.L. (2010). Beyond DCG: User behavior as a predictor of a successful search. Proc. WSDM, 221230.
8. He, B. and Ounis, I. (2006). Query performance prediction. Information Systems, 31(7): 585-594.
9. Huffman, S. and Hochster, M. (2007). How well does result relevance predict session satisfaction? Proc. SIGIR, 567-574.
10. Kelly, D. and Belkin, N.J. (2001). Reading time, scrolling, and interaction: Exploring implicit sources of user preferences for relevance feedback. Proc. SIGIR, 408-409.
11. Kelly, D. and Belkin, N.J. (2004). Display time as implicit feedback: Understanding task effects. Proc. SIGIR, 377-384.
12. Kim, Y., Hassan, A., White, R.W., and Zitouni, I. (2014). Modeling dwell time to predict click-level satisfaction. Proc. WSDM, 193-202.
13. Liu C., White, R.W., and Dumais, S. (2010). Understanding web browsing behaviors through Weibull analysis of dwell time. Proc. SIGIR. 379-386.
14. Wang, K., Thrasher, C., Viegas, E., Li, X. and Hsu, P. (2010). An overview of Microsoft web n-gram corpus and applications. NAACL HLT Demo Session, 45-48.
15. White, R.W. and Kelly, D. (2006). A study on the effects of personalization and task information on implicit feedback performance. Proc. CIKM, 297-306.
16. White, R.W. and Singla, A. (2011). Finding our way on the Web: Exploring the role of waypoints in search interaction, Proc. WWW, 147-148.
17. Xu, S., Jiang, H., and Lau, F.C.M. (2011). Mining user dwell time for personalized web search re-ranking. Proc. IJCAI, 2367-2372.