Nicholas J. Belkin
Abstract
Although we see the positive results of information retrieval research embodied throughout the Internet, on our computer desktops, and in many other aspects of daily life, at the same time we notice that people still have a wide variety of difficulties in finding information that is useful in resolving their problematic situations. This suggests that there still remain substantial challenges for research in IR. Already in 1988, on the occasion of receiving the ACM SIGIR Gerard Salton Award, Karen Spärck Jones suggested that substantial progress in information retrieval was likely only to come through addressing issues associated with users (actual or potential) of IR systems, rather than continuing IR research's almost exclusive focus on document representation and matching and ranking techniques. In recent years it appears that her message has begun to be heard, yet we still have relatively few substantive results that respond to it. In this paper, I identify and discuss a few challenges for IR research which fall within the scope of association with users, and which I believe, if properly addressed, are likely to lead to substantial increases in the usefulness, usability and pleasurability of information retrieval.
- Arapakis, I. & Jose, J. (2008) Affective Feedback: An investigation of the role of emotions during an information seeking process. In SIGIR 2008. Proceedings of the 31st Annual ACM SIGIR International Conference on Research and Development in Information Retrieval (in press). New York: ACM. Google Scholar
Digital Library
- Borlund, P. (2003). The IIR Evaluation Model: a Framework for Evaluation of Interactive Information Retrieval Systems. In: Information Research, vol. 8, no. 3, paper no. 152. {Available at: http://informationr.net/ir/8-3/paper152.html}Google Scholar
- Budzik, J. and Hammond, K. J. (2000) User Interactions with Everyday Applications as Context for Just-in-Time Information Access. In IUI 2000, ACM Conference on Intelligent User Interfaces (pp. 44--51). New York: ACM. Google ScholarDigital Library
- Cool, C. & Belkin, N. J. (2002). A classification of interactions with information. In Proceedings of the Fourth International Conference on Conceptions of Library and Information Science (pp. 1--15). Greenwood Village, CO: Libraries Unlimited.Google Scholar
- Fuhr, N. (2008) A probability ranking principle for interactive information retrieval. Information Retrieval, v. 11: 251--265. Google ScholarDigital Library
- Ingwersen, P. & Jäärvelin, K. (2005). The turn. Integration of information seeking and retrieval in context. Dordrecht: Springer. Google ScholarDigital Library
- Järvelin, K., Price, S. L., Delcambre, L. M. L. & Nielsen, M. L. Discounted Cumulated Gain Based Evaluation of Multiple-Query IR Sessions. In ECIR 2008, Proceedings of the 2008 European Conference on Information Retrieval (pp. 4--15). Berlin: Springer Verlag. Google ScholarDigital Library
- Kelly, D. (2005). Implicit feedback: Using behavior to infer relevance. In A. Spink and C. Cole (Eds.) New Directions in Cognitive Information Retrieval (pp. 169--186). Berlin: Springer Verlag.Google Scholar
- Kelly, D. & Belkin, N. J. (2004). Display time as implicit feedback: Understanding task effects. In SIGIR 2004, Proceedings of the 27th Annual ACM International Conference on Research and Development in Information Retrieval (pp. 377--384). New York: ACM. Google ScholarDigital Library
- Kelly, D. & Teevan, J. (2003). Implicit feedback for inferring user preference: A bibliography. SIGIR Forum, 37(2), 18--28. Google ScholarDigital Library
- Kuhlthau, C. C. (1991). Inside the search process: information seeking from the user's perspective. Journal of the American Society for Information Science, 42, 361--371.Google ScholarCross Ref
- Nahl, D. & Bilal, D. eds (2007) Information and emotion: The Emergent Affective Paradigm in Information Behavior Research and Theory. Medford, NJ: Information Today for ASIST.Google Scholar
- Olston, C. & Chi, Ed H. (2003). ScentTrails: Integrating browsing and searching on the web. ACM Tarnsactions on Computer-Human Interaction, 10(3), 177--197. Google ScholarDigital Library
- Robertson, S. E. & Hancock-Beaulieu, M. (1992) On the evaluation of IR systems. Information Processing and Management, v. 28(4): 457--466. Google ScholarDigital Library
- Saracevic, T (1997) Users lost: reflections of the past, future and limits of information science. SIGIR Forum, 31, 2: 16--27. Google ScholarDigital Library
- Spärck Jones, K. (1988) A look back and a look forward. In: SIGIR '88. Proceedings of the 11th Annual ACM SIGIR International Conference on Research and Development in Information Retrieval (pp. 13--29). New York: ACM. Google ScholarDigital Library
- Spärck Jones, K. (2005). Meta-reflections on TREC. In E. M. Voorhees & D. K. Harman (Eds.) TREC: Experiment and Evaluation in Information Retrieval (pp. 421--448). Cambridge, MA: MIT Press.Google Scholar
Teevan, J., Dumais, S. T. & Liebling, D. J. (2008) To personalize or not to personalize. In< SIGIR 2008. Proceedings of the 31st Annual ACM SIGIR International Conference on Research and Development in Information Retrieval (in press). New York: ACM. Google ScholarDigital Library- Turpin, A. H. & Hersh, W. (2001) Why batch and user evaluations do not give the same results. In SIGIR 2001, Proceedings of the 24th Annual ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 225--231). New York: ACM. Google ScholarDigital Library
- Turpin, A. & Scholer, F. (2006) User performance versus precision measures for simple search tasks. In SIGIR 2006, Proceedings of the 29th Annual ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 11--18). New York: ACM. Google ScholarDigital Library
- White, R. W. & Kelly, D. (2006). A study on the effects of personalization and task information on implicit feedback performance. In CIKM '06, Conference on Information and Knowledge Management (pp.). New York: ACM. Google ScholarDigital Library
Index Terms
- Some(what) grand challenges for information retrieval
Recommendations
Fuzzy information retrieval in WWW: a survey
Information retrieval has been an integral domain of storage and retrieval of meaningful information from the early age of computing. The last 15 years has seen a drastic shift of paradigm from classical database retrieval to web-based information ...
Information Retrieval System: An Overview, Issues, and Challenges
Information Retrieval Systems IRS have dramatically changed the ways how people acquire information for their need. Information Retrieval IR enables user to find relevant document from collection of countless resources. This article presents an overview ...
Comments