Abstract
In this paper, we advance a technique to develop a user profile for information retrieval through knowledge acquisition techniques. The profile bridges the discrepancy between user-expressed keywords and system-recognizable index terms. The approach presented in this paper is based on the application of personal construct theory to determine a user's vocabulary and his/her view of different documents in a training set. The elicited knowledge is used to develop a model for each phrase/concept given by the user by employing machine learning techniques.
Our model correlates the concepts in a user's vocabulary to the index terms present in the documents in the training set. Computation of dependence between the user phrases also contributes in the development of the user profile and in creating a classification of documents. The resulting system is capable of automatically identifying the user concepts and query translation to index terms computed by the conventional indexing process. The system is evaluated by using the standard measures of precision and recall by comparing its performance against the performance of the smart system for different queries.
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Bhatia, S.K., Deogun, J.S., and Raghavan, V.V. (1990). Assignment of Term Descriptors to Clusters.In Proceedings of the 1990 Symposium on Applied Computing (pp. 181–185). Fayetteville, AR, IEEE Computer Society Press.
Bhatia, S.K., Deogun, J.S., and Raghavan, V.V. (1990). Automatic Rule-Base Generation for User-Oriented Information Retrieval. InISMIS'90: Proceedings of the Fifth International Symposium on Methodologies for Intelligent Systems (pp. 118–125). Knoxville, TN, North-Holland.
Bhatia, S.K., Deogun, J.S., and Raghavan, V.V. (1991). User Profiles for Information Retrieval. In Z.W. Ras and M. Zemankova (Eds.),Methodologies for Intelligent Systems: 6th International Symposium, ISMIS'91 (pp. 102–111). Charlotte, NC, Springer-Verlag. Lecture Notes in Artificial Intelligence # 542.
Boose, J.H. (1985). A Knowledge Acquisition Program for Expert System Based on Personal Construct Theory.International Journal of Man-Machine Studies, 23, 495–525.
Boose, J.H. (1985). Personal Construct Theory and the Transfer of Human Expertise. In T.O'Shea (Ed.),Advances in Artificial Intelligence (pp. 51–60). Elsevier-Science Publishers B. V. (North-Holland).
Boose, J.H. (1986).Expertise Transfer for Expert System Design. Elsevier-Science Publishers, New York.
Boose, J.H. (1989). A Survey of Knowledge Acquisition Techniques and Tools.Knowledge Acquisition, 1(1), 3–37.
Buckley, C. (1985). Implementation of the smart Information Retrieval System. Technical Report TR 85-686, Cornell University, Department of Computer Science, Ithaca, NY.
Chow, C.K. and Liu, C.N. (1968). Approximating Discrete Probability Distributions with Dependence Trees.IEEE Transactions on Information Theory, IT-14, 462–467.
Deogun, J.S. Bhatia, S.K., and Raghavan, V.V. (1991). Automatic Cluster Assignments for Documents. InProceedings of the Seventh IEEE Conference on Artificial Intelligence Applications. Miami Beach, FL.
Deogun, J.S. and Raghavan, V.V. (1991). UNL/USL: MUC-3 Test Results and Analysis. In B. Sundheim (Ed.),Proceedings of the Third Message Understanding Conference. San Diego, CA.
Deogun, J.S., Raghavan, V.V., and Bhatia, S.K. (1989). A Theoretical Basis for the Automatic Extraction of Relationships from Expert-Provided Data. InISMIS'89: Proceedings of the Fourth International Symposium on Methodologies for Intelligent Systems: Poster Session (pp. 123–131). Charlotte, NC.
Ford, K.M. and Chang, P.J. (1989). An Approach to Automated Knowledge Acquisition Founded on Personal Construct Theory. In M. Fishman (Ed.),Advances in Artificial Intelligence. JAI Press, Greenwich, CT.
Ford, K.M. and Perry, F.E. (1987). The Production of Expert System Rules from Repertory Grid Data Based on A Logic of Confirmation. InSeventh International Congress on Personal Construct Psychology. Memphis, TN.
Gammack, J.G. (1987). Different Techniques and Different Aspects on Declarative Knowledge. In A.L. Kidd (Ed.),Knowledge Acquisition for Expert Systems: A Practical Handbook (pp. 137–163). Plenum Press, New York, NY.
Hart, A. (1986).Knowledge Acquisition for Expert Systems. McGraw-Hill, New York, NY.
Kelly, G.A. (1955).The Psychology of Personal Constructs. Norton Publishers, New York, NY.
Kodratoff, Y., Manago, M., and Blythe, J. (1988). Generalization and Noise. In B.R. Gaines and J.H. Boose (Eds.),Knowledge Acquisition for Knowledge-Based Systems (vol. 1) (pp. 301–324). Academic Press, San Diego, CA.
Kok, A.J. and Botman, A.M. (1988). Retrieval Based on User Behavior. InProceedings of the Eleventh International Conference on Research and Development in Information Retrieval (pp. 343–357). Grenoble, France.
Korfhage, R.R. and Chavarria-Garza, H. (1982). Retrieval Improvement by the Interaction of Queries and User Profiles. InCOMPSAC 82: IEEE Computer Society's Sixth International Computer Software & Applications Conference (pp. 470–475). Chicago, IL.
McCune, B.P., Tong, R.M., Dean, J.S., and Shapiro, D.G. (1985). RUBRIC: A System for Rule-based Information Retrieval.IEEE Transactions on Software Engineering, SE-11(9), 939–945.
Shaw, M.L.G. and Gaines, B.R. (1987). An Interactive Knowledge-Elicitation Technique Using Personal Construct Technology. In A.L. Kidd (Ed.),Knowledge Acquisition for Expert Systems: A Practical Handbook (pp. 109–136). Plenum Press, New York, NY.
Tong, R.M., Askman, V.N., Cunningham, J.F., and Tollander, C.J. (1985). RUBRIC: An Environment for Full Text Information Retrieval. InProceedings of the Eighth International ACM Conference on R&D in Information Retrieval. Montreal, Canada.
Tong, R.M. and Shapiro, D.G. (1985). Experimental Investigations of Uncertainty in A Rule-Based System for Information Retrieval.International Journal of Man-Machine Studies, 22, 265–282.
van Rijsbergen, C.J. (1981).Information Retrieval. Butterworth Publishers, Boston, MA, 2nd edition.
van Rijsbergen, C.J., Harper, D.J., and Porter, M.F. (1981). The Selection of Good Search Terms.Information Processing and Management, 17, 77–91.
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This research is supported by the NSF grant IRI-8805875.
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Bhatia, S.K., Deogun, J.S. & Raghavan, V.V. Conceptual query formulation and retrieval. J Intell Inf Syst 5, 183–209 (1995). https://doi.org/10.1007/BF00962233
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DOI: https://doi.org/10.1007/BF00962233