SP500207 TIPSTER Panel -- HNC's MatchPlus System chapter S. Gallant R. Hecht-Nielson W. Caid K. Qing J. Carleton D. Sudbeck National Institute of Standards and Technology Donna K. Harman * cluster tree speedup for retrieval * different term weighting methods for document and query context vector creation, as well as for bootstrapping. Although young, we believe MatchPlus has already shown encouraging results, and we look forward to growing it. References [[OCRerr] Gallant S. I. Context Vector Representa- tions for Document Retrieval. AAAI-91 Natu- ral Language Text Retrieval Workshop, Ana- heim, CA, July 15, 1991. [2] Gallant, S. I. A Practical Approach for Representing Context And for Performing Word Sense Disambiguation Using Neural Networks. Neural Computation, Vol.3, No. 3, 1991, 293-309. [3] Hinton, G. E. Distributed Representations. Technical Report CMU-CS-84-157, Carnegie- Mellon University, Department of Computer Science. Revised version in Rumelhart, D. E. & McClellaiid, J. L. (Eds.) Parallel Dis- tributed Processing: Explorations in the Mi- crostructures of Co9nition, Vol.1. MIT Press, 1986. [4] Salton, G. The SMART retrieval s[OCRerr]tem - Ex- perirnents in automatic automatic document processing. Englewood Cliffs, NJ: Prentice- Hall, 1971. [5] Salton, G. & Buckley, C. Term-Weighting Ap- proaches in Automatic Text Retrieval. Infor- mation Processing & Management, Vol.24, No.5, 1988, pp.513-523. [6] Salton, G. & Buckley, C. Improving Retrieval Performance by Relevance Feedback. Journal of the American Society for Information Sci- ence, 41(4):288-297, 1990. [7] Waltz, D. L. & Pollack, J. B. Massively Par- allel Parsing: A Strongly Interactive Model of Natural Language Interpretation. Cogni- tive Science 9, 51-74 (1985). 111