Abstract
Computer users often experience the “lost in informationspace” syndrome. Information filtering suggests a solution based onrestricting the amount of information made available to users. Thisstudy suggests an advanced model for information filtering which isbased on a two-phase filtering process. The user profiling in themodel is constructed on the basis of the user's areas of interestand on sociological parameters about him that are known to thesystem. The system maintains a database of known stereotypes thatincludes rules on their information retrieval needs and habits.During the filtering process, the system relates the user to one ormore stereotypes and operates the appropriate stereotypic rules.
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References
Belkin, N.J. and Croft, W.B. (1992). Information Filtering and Information Retieval: Two Sides of the Same Coin? Communication of the ACM, 35(12), 29–38.
Brajnik, G., Guida, G., and Tasso, C. (1990). User Modeling in Expert Man-Machine Interfaces: A Case Study in Intelligent Information Retrieval, IEEE Transactions on Systems, Man and Cybernetics, 20(1), 166–185.
Chin, D.N. (1989). KNOME: Modeling What the User Knows in UC. In Alfred Kobsa and Wolfgang Wahster (Eds.), User Models in Dialog Systems. Berlin: Springer-Verlag, pp. 74–107.
Finin, W. (1989). GUMS: A General User Modeling Shell. In Alfred Kobsa and Wolfgang Wahster (Eds.), User Models in Dialog Systems. Berlin: Springer-Verlag, pp. 411–430.
Foltz, P.W. and Dumais, S.T. (1992). Personalized Information Delivery: An Analysis of Information Filtering Methods, Communication of the ACM, 35(12), 51–60.
Malone, T., Grant, K., Turbak, F., Brobst, S., and Cohen, M. (1987). Intelligent Information Sharing Systems, Communication of the ACM, 30(5), 390–402.
McCleary, H. (1994). Filtered Information Services, A Revolutionary New Product or a New Marketing Strategy? Online, 4(18), 33–42.
Morita, M. and Shinoda, Y. (1994). Information Filtering Based on User Behavior Analysis and Best Match Retrieval, ACM-SIGIR, pp. 272–281.
Rich, E. (1983). Artificial Intelligence, McGraw-Hill Series in AI. New-York, pp. 361–387.
Rich, E. (1989). Stereotypes and User Modeling. In Alfred Kobsa and Wolfgang Wahster (Eds.), User Models in Dialog Systems. Berlin: Springer-Verlag, Chap. 2, pp. 75–85.
Salton, G. and McGill, W.J. (1983). Introduction to Modern Information Retrieval. New-York: Mcgraw-Hill.
Shapira, B., Shoval, P., Raveh, A., and Hanani, U. (1996). Hypertext Browsing: A New Model for Information Filtering Based on User Profiles and Data Clustering, Online & CDROM Review, 20(1), 3–10.
Shardanand, U. (1994). Social Information Filtering for Music Recomendation, MIT EECS M.Eng. thesis. also TR-94-04, Learning and CommonSense Group, MIT Media Laboratory.
Stadnyk, I. and Kass, R. (1992). Modeling Users’ Interests in Information Filters, Communication of the ACM, 35(12), 49–50.
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Shapira, B., Hanani, U., Raveh, A. et al. Information Filtering: A New Two-Phase Model Using Stereotypic User Profiling. Journal of Intelligent Information Systems 8, 155–165 (1997). https://doi.org/10.1023/A:1008676625559
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DOI: https://doi.org/10.1023/A:1008676625559