- 1.BOLLMANN, P., }OCHUM, F., REINEa, U., WEISS- MANN, V., AND ZUSE, H. The LIVE project" Retrieval experiments based on evaluation viewpoints, in Proceedings of the 8th Annual International A CM/SIGIR Conference on Research and Development in Information Retrieval (Montreal, 1985), pp. 213-214. Google ScholarDigital Library
- 2.BOLLMANN-SDORRA, P., AND RAGHAVAN, V. V. Oil the delusiveness of adopting a common space for modeling IR objects: Are queries documents ? J. of the American Society for Information Science ~, 10 (1993), 579-587. Google ScholarDigital Library
- 3.BOOKSTEn~, A., AND COOPER, W. A general mathematical models for information retrieval systems. Library Querterly 4a, 2 (1976), 153-167.Google Scholar
- 4.DAS-GUPTA, P. Rough sets and information retrieval. In Proc. of 11th International Conference on Research and Development in information Retrieval (New York, NY, 1988), ACM, pp. 567-581. Google ScholarDigital Library
- 5.DUDA, R. O., AND HART, P. E. Pattern Classification and Scene Analysis. John Wiley & Sons, 1973.Google Scholar
- 6.ISMAm, M. A., AND KAMEL, M. S. Multidimensional data clustering: Utilizing hybrid search strategies. Pattern Recognition 22 (1989), 75-89. Google ScholarDigital Library
- 7.JONES, K. S. Automatic Keyword Classification :forGoogle Scholar
- 8.JUNG, G. S. Connectionist Domain Knowledge ~Acquisition and its Evaluation in information Retrieval. PhD thesis, The University of Southwestern Louisiana, 1991. Google ScholarDigital Library
- 9.MINSKY, M., AND PAPERT, S. Perceptrons-an introduction to computational geometry. MIT Press, 1969. Google ScholarDigital Library
- 10.RAGHAVAN, V. V. Clustering algorithms for information retrieval: An AI perspective. In Proc. of 9th Annual Hawaii International Conference on System Sciences (Honolulu, HI, 1986), pp. 142-151.Google Scholar
- 11.RAGHAVAN, V. V., AND DP.OGUN, J. S. Information retrieval research: Strategies and user implications. Information Technology: Research and Development, 1 (1982), 157-171.Google Scholar
- 12.ROBERTS, F.S. Discrete Mathematical Models. Prentice-Hall, Inc., 1976.Google Scholar
- 13.ROBERTSON, S. E., AND JONES, K. S. Relevance weighting of search terms. J. o} the American Society for Info. Science (may-jun 1976), 129-146.Google Scholar
- 14.SALTON, G. Automatic Text Processing. Addison- Wesley, 1988. Google ScholarDigital Library
- 15.SALTON, G., AND BUCKLEY, C. Term-weighting approaches in automatic text retrieval. Information Processing ~ Management 24, 5 (1988), 513-523. Google ScholarDigital Library
- 16.VAN RIJSBERGEN, C. J. Information Retrieval. Butterworths, London, UK, 1975. Google ScholarDigital Library
- 17.WONG, S. K. M., AND YAO, Y. Y. Query formulation in linear retrieval models. J. of the American Society .for In}o. Science 41, 5 (1990), 334-341.Google Scholar
- 18.WONG, S. K. M., YAO, Y. Y., AND BOLLMANN, P. Linear structure in information and retrieval. In Proc. o} 14th ACM-SIGIR Con}. (Grenoble, France, 1988), pp. 219-232. Google ScholarDigital Library
- 19.WONG, S. K. M., ZIARKO, W., RAGHAVAN, V. V., AND WONG, e. C. N. Extended boolean query processing in the generalized vector space model, inlormation Systems 14, 1 (1989), 47-63. Google ScholarDigital Library
- 20.ZHANG, Y., R.AGHAVAN, V. V., AND DEOGUN, J. S. An object-oriented modeling of history of optimal retrievals. In Proc. of the 14th Int'l. A CM-SIGIR Con}. on Research and Development in Information Retrieval (Chicago, IL, Oct 1991), pp. 241-250. Google ScholarDigital Library
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- On the reuse of past optimal queries
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