ABSTRACT
Understanding the extent to which people's search behaviors differ in terms of the interaction flow and information targeted is important in designing interfaces to help World Wide Web users search more effectively. In this paper we describe a longitudinal log-based study that investigated variability in people.s interaction behavior when engaged in search-related activities on the Web.allWe analyze the search interactions of more than two thousand volunteer users over a five-month period, with the aim of characterizing differences in their interaction styles.allThe findings of our study suggest that there are dramatic differences in variability in key aspects of the interaction within and between users, and within and between the search queries they submit.allOur findings also suggest two classes of extreme user. navigators and explorers. whose search interaction is highly consistent or highly variable. Lessons learned from these users can inform the design of tools to support effective Web-search interactions for everyone.
- Bates, M. (1989). The design of browsing and berrypicking techniques for the online search interface. Online Review, 13: 407--424.Google ScholarCross Ref
- Bederson, B.B. & Shneiderman, B. (2003). The Craft of Information Visualization: Readings and Reflections. Morgan Kaufmann. Google ScholarDigital Library
- Bhavnani, S.K. (2001). Domain-specific search strategies for the effective retrieval of healthcare and shopping information. In Proc. CHI 2002, 610--611. Google ScholarDigital Library
- Buckland, M.K. & Florian, D. (1991). Expertise, task complexity, and artificial intelligence: A conceptual framework. J. Amer. Soc. Info. Sci, 42 (9), 635--643.Google ScholarCross Ref
- Card, S.K. et al. (2001). Information scent as a driver of web behavior graphs: Results of a protocol analysis method for web usability. In Proc. CHI 2001, 498--505. Google ScholarDigital Library
- Catledge, L.D. & Pitkow, J.E. (1995). Characterizing browsing strategies in the world wide web. Computer Networks and ISDN Systems, 27(6): 1065--1073. Google ScholarDigital Library
- Chi, E., Pirolli, P., Chen, J., Pitkow, J. (2001).allUsing information scent to model user information needs and actions on the web. In Proc. CHI 2001, pp. 490--497. Google ScholarDigital Library
- Cutrell, E. et al. (2006). Fast, flexible filtering with Phlat -- Personal search and organization made easy. In Proc. CHI 2006, 261--270. Google ScholarDigital Library
- Dillon, A. & Watson, C. (1996). User analysis in HCI: the historical lesson from individual differences research. International Journal of Human-Computer Studies, 45(6): 619--637. Google ScholarDigital Library
- Egan, D. (1988) Individual differences in human-computer interaction. In: Handbook of Human-computer Interaction. Elsevier, 543--568.Google ScholarCross Ref
- Eisenstein, J. & Rich, R. (2002). Agents and GUIs from task models. In Proc. IUI 2002, 47--54. Google ScholarDigital Library
- Ford, N. et al. (2002). Information seeking and mediated searching. Part 4. Cognitive styles in information seeking. JASIST, 53(9), 728--35. Google ScholarDigital Library
- Hölscher, C. & Strube, G. (2000). Web search behavior of Internet experts and newbies. Computer Networks, 33, 337--46. Google ScholarDigital Library
- Huberman, B. et al. (1998). Strong regularities in World Wide Web surfing. Science, 280 (5360): 95--97.Google ScholarCross Ref
- Jansen, B. J., Spink, A. & Saracevic, T. (2000). Real life, real users, and real needs: A study and analysis of user queries on the Web. Info. Proc. & Mgt., 36: 207--227. Google ScholarDigital Library
- Jones, R. et al. (2006). Generating query substitutions. In Proc. WWW 2006, 387--396. Google ScholarDigital Library
- Lau, T. & Horvitz, E. (1999). Patterns of search: Analyzing and modeling web query refinement. In Proc. UM 1999, 119--128. Google ScholarDigital Library
- Levenshtein, V. (1966). Binary codes capable of correcting deletions, insertions and reversals. Soviet Physics Doklady, 10(8):707--710.Google Scholar
- Lieberman, H.L., Fry, C. & Weitzman, L. (2001). Exploring the Web with reconnaissance agents. Communications of the ACM, 44(8): 69--75. Google ScholarDigital Library
- Malone, T.E. (1983). How do people organize their desks? ACM TOIS, 1(1): 99--112. Google ScholarDigital Library
- Marchionini, G. (1995). Information seeking in electronic environments. Cambridge University Press. Google ScholarDigital Library
- Milic-Frayling, N. (2004). SmartBack: Supporting users in back navigation. In Proc. WWW 2004, 63--71. Google ScholarDigital Library
- Neilsen, J. (1993). Usability Engineering, Cambridge MA: Academic Press.Google Scholar
- Newell, A. & Simon, H. (1972). Human Problem Solving. Prentice-Hall. Google ScholarDigital Library
- O'Day, V. & Jeffries, R. (1993). Orienteering in an information landscape: how information seekers get from here to there. In Proc. CHI 1993, 438--445. Google ScholarDigital Library
- Pask, G. (1976). Conventional techniques in the study and practice of education. British Journal of Educational Psychology, 46, 12--25.Google ScholarCross Ref
- Pirolli, P. & Card, S.K. (1995). Information foraging. Psychological Review, 106, 643--675.Google ScholarCross Ref
- Pirolli, P. & Fu, W. (2003). Snif-act: A model of information foraging on the World Wide Web. In Proc. UM 2003, 45--54. Google ScholarDigital Library
- Pitkow, J. & Pirolli, P. (1999). Mining longest repeating subsequences to predict World Wide Web surfing. In Proc. USENIX Symposium, 139--150. Google ScholarDigital Library
- Pitkow, J. et al. (2002). Personalized search. Communications of the ACM, 45(9): 50--55. Google ScholarDigital Library
- Rich, E. (1989). Stereotypes and user modeling. In User Models in Dialog Systems. Springer.Google Scholar
- Rose, D. E. & Levinson, D. (2004). Understanding user goals in Web search. In Proc. WWW 2004, 13--19. Google ScholarDigital Library
- Russell, D.M. et al. (1993). The cost structure of sensemaking. In Proc. CHI 1993, 269--276. Google ScholarDigital Library
- Tauscher, L. & Greenberg, S. (1997). Revisitation patterns in World Wide Web navigation. In Proc. CHI 1997, 399--406. Google ScholarDigital Library
- Teevan, J. et al. (2006). History repeats itself: Repeat queries in Yahoo's logs. In Proc. SIGIR 2006, 703--704. Google ScholarDigital Library
- Teevan, J. et al. (2004). The perfect search engine is not enough: A study of orienteering behavior in directed search. In Proc. CHI 2004, 415--422. Google ScholarDigital Library
- Teevan, J. et al. (2005). Beyond the commons: Investigating the value of personalizing web search. In Proc. PIA 2005.Google Scholar
- Trigg, R.H. (1988). Guided tours and tabletops: tools for communicating in a hypertext environment. Transactions on Information Systems, 6(4): 398--414. Google ScholarDigital Library
- Weinreich, H., Obendorf, H., Herder, E. & Mayer, M. (2006). Off the beaten tracks: Exploring three aspects of web navigation. In Proc. WWW 2006, 133--142. Google ScholarDigital Library
- Wexelblat, A. & Maes, P. (1999). Footprints: History-rich tools for information foraging. In Proc. CHI 1999, 270--277. Google ScholarDigital Library
Index Terms
- Investigating behavioral variability in web search
Recommendations
Improving Ranking Consistency for Web Search by Leveraging a Knowledge Base and Search Logs
CIKM '15: Proceedings of the 24th ACM International on Conference on Information and Knowledge ManagementIn this paper, we propose a new idea called ranking consistency in web search. Relevance ranking is one of the biggest problems in creating an effective web search system. Given some queries with similar search intents, conventional approaches typically ...
Identifying popular search goals behind search queries to improve web search ranking
AIRS'11: Proceedings of the 7th Asia conference on Information Retrieval TechnologyWeb users usually have a certain search goal before they submit a search query. However, many laypersons can't transform their search goals into suitable queries. Thus, understanding original search goals behind a query is very important for search ...
Web search engine multimedia functionality
Web search engines are beginning to offer access to multimedia searching, including audio, video and image searching. In this paper we report findings from a study examining the state of multimedia search functionality on major general and specialized ...
Comments