Abstract
This article presents a novel Web search interaction feature that for a given query provides links to Web sites frequently visited by other users with similar information needs. These popular destinations complement traditional search results, allowing direct navigation to authoritative resources for the query topic. Destinations are identified using the history of the search and browsing behavior of many users over an extended time period, and their collective behavior provides a basis for computing source authority. They are drawn from the end of users' postquery browse trails where users may cease searching once they find relevant information. We describe a user study that compared the suggestion of destinations with the previously proposed suggestion of related queries as well as with traditional, unaided Web search. Results show that search enhanced by query suggestions outperforms other systems in terms of subject perceptions and search effectiveness for fact-finding search tasks. However, search enhanced by destination suggestions performs best for exploratory tasks with its best performance obtained from mining past user behavior at query-level granularity. We discuss the implications of these and other findings from our study for the design of search systems that utilize user behavior, in particular, user browse trails and popular destinations.
- Agichtein, E., Brill, E., and Dumais, S. 2006b. Improving Web search ranking by incorporating user behavior information. In Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval. 19--26. Google Scholar
Digital Library
- Agichtein, E., Brill, E., Dumais, S., and Ragno, R. 2006a. Learning user interaction models for predicting Web search result preferences. In Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval. 3--10. Google Scholar
Digital Library
- Anderson, C., Domingos, P., and Weld, D. S. 2001. Adaptive Web navigation for wireless devices. In Proceedings of the International Joint Conference on Artificial Intelligence. 879--884. Google Scholar
Digital Library
- Anick, P. 2003. Using terminological feedback for Web search refinement: A log-based study. In Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval. 88--95. Google Scholar
Digital Library
- Beaulieu, M. 1997. Experiments with interfaces to support query expansion. J. Documen. 53, 1, 8--19.Google Scholar
Cross Ref
- Beeferman, D. and Berger, A. 2000. Agglomerative clustering of a search engine query log. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 407--416. Google Scholar
Digital Library
- Bilenko, M. and White, R. W. 2008. Mining the search trails of the surfing crowds: Identifying authoritative sources from user activity. In Proceedings of the World Wide Web Conference. 51--60. Google Scholar
Digital Library
- Borlund, P. 2000. Experimental components for the evaluation of interactive information retrieval systems. J. Documen. 56, 1, 71--90.Google Scholar
Cross Ref
- Bush, V. 1945. As we may think, Atlantic Monthly 3, 2, 37--46. Google Scholar
Digital Library
- Card, S. K., Pirolli, P., Van Der Wege, M., Morrison, J., Reeder, R. W., Schraedly, P. K. and Boshart, J. 2001. Information scent as a driver of Web behavior graphs: Results of a protocol analysis method for Web usability. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. 498--505. Google Scholar
Digital Library
- Catledge, L. D. and Pitkow, J. E. 1995. Characterizing browsing strategies in the world wide web. Comput. Netw. ISDN Syst. 27, 6, 1065--1073. Google Scholar
Digital Library
- Chalmers, M., Rodden, K., Brodbeck, D. 1998. The order of things: Activity-centered information access. In Proceedings of the World Wide Web Conference. 359--367. Google Scholar
Digital Library
- Craswell, N. and Szummer, M. 2007. Random walks on the click graph. In Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval. 239--246. Google Scholar
Digital Library
- Croft, W. B. and Thompson, R. H. 1987. I3R: A new approach to the design of document retrieval systems. J. Amer. Soc. Inform. Sci. Techn. 38, 6, 389--404. Google Scholar
Digital Library
- Downey, D., Dumais, S., and Horvitz, E. 2007. Models of searching and browsing: Languages, studies and applications. In Proceedings of the International Joint Conference on Artificial Intelligence. 1465--1472. Google Scholar
Digital Library
- Dumais, S. T. and Belkin, N. J. 2005. The TREC interactive tracks: Putting the user into search. In E. M. Voorhees and D. K. Harman, Eds. TREC: Experiment and Evaluation in Information Retrieval, MIT Press, Cambridge, MA, 123--153.Google Scholar
- Fox, S., Karnawat, K., Mydland, M., Dumais, S., and White, T. 2005. Evaluating implicit measures to improve Web search. ACM Trans. Inform. Syst. 23, 2, 147--168. Google Scholar
Digital Library
- Furnas, G. W. 1985. Experience with an adaptive indexing scheme. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. 131--135. Google Scholar
Digital Library
- Furnas, G. W., Landauer, T. K., Gomez, L. M., and Dumais, S. T. 1987. The vocabulary problem in human-system communication. Commun. ACM 30, 11, 964--971. Google Scholar
Digital Library
- Hickl, A., Wang, P., Lehmann, J., and Harabagiu, S. 2006. FERRET: Interactive question-answering for real-world environments. In Proceedings of COLING/ACL. 25--28. Google Scholar
Digital Library
- Jansen, B. J. and Spink, A. 2005. How are we searching the World Wide Web? A comparison of nine search engine transaction logs. Inform. Proces. Manag. 42, 1, 248--263. Google Scholar
Digital Library
- Joachims, T. 2002. Optimizing search engines using clickthrough data. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 133--142. Google Scholar
Digital Library
- Joachims, T., Granka, L. A., Pan, B., Hembrooke, H., and Gay, G. 2005. Accurately interpreting clickthrough data as implicit feedback. In Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval. 154--161. Google Scholar
Digital Library
- Jones, R., Rey, B., Madani, O., and Greiner, W. 2006. Generating query substitutions. In Proceedings of the World Wide Web Conference. 387--396. Google Scholar
Digital Library
- Kleinberg, J. 1998. Authoritative sources in a hyperlinked environment. In Proceedings of the ACM-SIAM Symposium on Discrete Algorithms. 668--677. Google Scholar
Digital Library
- Koenemann, J. and Belkin, N. 1996. A case for interaction: A study of interactive information retrieval behavior and effectiveness. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. 205--212. Google Scholar
Digital Library
- Newell, A. and Simon, H. 1972. Human Problem Solving. Prentice-Hall, Englewood Cliffs, NJ. Google Scholar
Digital Library
- O'day, V. and Jeffries, R. 1993. Orienteering in an information landscape: How information seekers get from here to there. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. 438--445. Google Scholar
Digital Library
- Pirolli, P., Pitkow, J., and Rao, R. 1996. Silk from a sow's ear: Extracting usable structures from the Web. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. 118--125. Google Scholar
Digital Library
- Pitkow, J. and Pirolli, P. 1997. Life, death, and lawfulness on the electronic frontier. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. 383--390. Google Scholar
Digital Library
- Pitkow, J. and Pirolli, P. 1999. Mining longest repeating subsequences to predict World Wide Web surfing. In Proceedings of the USENIX Symposium. 139--150. Google Scholar
Digital Library
- Radlinksi, F. and Joachims, T. 2005. Query chains: Learning to rank from implicit feedback. In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 239--248. Google Scholar
Digital Library
- Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., and Riedl, J. 2005. GroupLens: An open architecture for collaborative filtering of netnews. In Proceedings of the ACM Conference on Computer Supported Cooperative Work. 175--186. Google Scholar
Digital Library
- Salton, G. and Buckley, C. 1988. Term-weighting approaches in automatic text retrieval. Inform. Proces. Manag. 24, 5, 513--523. Google Scholar
Digital Library
- Sarwar, B. M., Karypis, G., Konstan, J. A., and Riedl, J. 2000. Analysis of recommendation algorithms for e-commerce. In Proceedings of the ACM Conference on Electronic Commerce. 158--167. Google Scholar
Digital Library
- Shardanand, U. and Maes, P. 1995. Social information filtering: Algorithms for automating word of mouth. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. 210--217. Google Scholar
Digital Library
- Silverstein, C., Marais, H., Henzinger, M., and Moricz, M. 1999. Analysis of a very large Web search engine query log. SIGIR Forum 33, 1, 6--12. Google Scholar
Digital Library
- Smucker, M. and Allan, J. 2006. Find-similar: Similarity browsing as a search tool. In Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval. 461--468. Google Scholar
Digital Library
- Smyth, B., Balfe, E., Freyne, J., Briggs, P., Coyle, M., and Boydell, O. 2004. Exploiting query repetition and regularity in an adaptive community-based Web search engine. User Model. User Adapt. Interact. 14, 5, 382--423. Google Scholar
Digital Library
- Teevan, J., Alvarado, C., Ackerman, M. S., and Karger, D. R. 2004. The perfect search engine is not enough: A study of orienteering behavior in directed search. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. 415--422. Google Scholar
Digital Library
- Weinreich, H., Obendorf, H., Herder, E., and Mayer, M. 2006. Off the beaten tracks: Exploring three aspects of Web navigation. In Proceedings of the World Wide Web Conference. 133--142. Google Scholar
Digital Library
- Wexelblat, A. and Maes, P. 1999. Footprints: history-rich tools for information foraging. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. 270--277. Google Scholar
Digital Library
- White, R. W., Ruthven, I., Jose, J. M., and Van Rijsbergen, C. J. 2005. Evaluating implicit feedback models using searcher simulations. ACM Trans. Inform. Syst. 23, 3, 325--361. Google Scholar
Digital Library
- White, R. W. and Drucker, S. M. 2007. Investigating behavioral variability in Web search. In Proceedings of the World Wide Web Conference. 21--30. Google Scholar
Digital Library
- White, R. W. and Marchionini, G. 2007. Examining the effectiveness of real-time query expansion. Inform. Proces. Manage. 43, 3, 685--704. Google Scholar
Digital Library
- White, R. W., Bilenko, M., and Cucerzan, S. 2007. Studying the use of popular destinations to enhance Web search interaction. In Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval. 159--166. Google Scholar
Digital Library
- Xue, G.-R., Zeng, H.-J., Chen, Z., Yu, Y., Ma, W. Y., Xi, W., and Fan, W. 2004. Optimizing Web search using web click-through data. In Proceedings of ACM CIKM Conference on Information and Knowledge Management. 118--126. Google Scholar
Digital Library
- Zhai, C. and Lafferty, J. 2004. A study of smoothing methods for language models applied to information retrieval. ACM Trans. Inform. Syst. 22, 2, 179--214. Google Scholar
Digital Library
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Leveraging popular destinations to enhance Web search interaction
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