Abstract
Although relevance feedback techniques are relatively common in the field of information retrieval (IR), feedback usually supports a process of query refinement. Using feedback to restructure the information space itself has yet to be attempted. Restructuring not only supports useful applications such as clustering, but is also indispensable for IR given that the modeling function employs inter-term correlation. This paper presents a new approach to relevance feedback involving information space manipulation, and examines its effectiveness through a number of experiments.
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References
Rocchio, J, J.:Relevance feedback in information retrieval. The Smart Retrieval System-Experiments in Automatic Document Processing. Prentice-Hall.Inc (1971) 313–323
Buckley, C. and Salton, G.:Optimization of relevance feedback weights. Proc. of ACM SIGIR Conference on Research and Development in Information Retrieval (1995) 351–357
Harman, D.:Relevance feedback revisited. Proc.of ACM SIGIR Conference on Research and Development in Information Retrieval (1992) 1–10
V, V, Raghavan. and H, Sever.: On the reuse of past optimal queries. Proc.of ACM SIGIR. (1995) 344–350
C, T, Yu.: A Formal Construction of Term Classes. Journal of the ACM. (1975) 17–37
Salton, G., Allan, J. and Buckley, C.: Automatic Structuring and Retrieval of Large Text Files. Communications of the ACM, Vol.37. (1994) 97–108
Salton, G. and Buckley, C.: Term-Weighting Approaches In Automatic Text retrieval. Information Processing & Management, Vol.24. (1988) 515–523
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© 2000 Springer-Verlag Berlin Heidelberg
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Murakami, T., Orihara, R., Yokota, T. (2000). Friendly Information Retrieval through Adaptive Restructuring of Information Space. In: Logananthara, R., Palm, G., Ali, M. (eds) Intelligent Problem Solving. Methodologies and Approaches. IEA/AIE 2000. Lecture Notes in Computer Science(), vol 1821. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45049-1_77
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DOI: https://doi.org/10.1007/3-540-45049-1_77
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