Automatic Document Classification: Natural Language Processing, Statistical Analysis, and Expert System Techniques used together.

M. J. Blosseville, Georges Hébrail, M. G. Monteil, N. Pénot: Automatic Document Classification: Natural Language Processing, Statistical Analysis, and Expert System Techniques used together. SIGIR 1992: 51-58

@inproceedings{DBLP:conf/sigir/BlossevilleHMP92,
  author    = {M. J. Blosseville and
               Georges H{\'e}brail and
               M. G. Monteil and
               N. P{\'e}not},
  editor    = {Nicholas J. Belkin and
               Peter Ingwersen and
               Annelise Mark Pejtersen},
  title     = {Automatic Document Classification: Natural Language Processing,
               Statistical Analysis, and Expert System Techniques used together},
  booktitle = {Proceedings of the 15th Annual International ACM SIGIR Conference
               on Research and Development in Information Retrieval. Copenhagen,
               Denmark, June 21-24, 1992},
  publisher = {ACM},
  year      = {1992},
  isbn      = {0-89791-523-2},
  pages     = {51-58},
  ee        = {db/conf/sigir/BlossevilleHMP92.html},
  crossref  = {DBLP:conf/sigir/92},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

In this paper we describe an automated method of classifying research project descriptions: a human expert classifies a sample set of projects into a set of disjoint and pre-defined classes, and then the computer learns from this sample how to classify new projects into these classes. Both textual and non-textual information associated with the projects are used in the learning and classification phases. Textual information is processed by two methods of analysis: a natural language analysis followed by a statistical analysis. Non-textual information is processed by a symbolic learning technique. We present the results of some experiments done on real data: two different classifications of our research projects.

Copyright © 1992 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.

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Nicholas J. Belkin, Peter Ingwersen, Annelise Mark Pejtersen (Eds.): Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Copenhagen, Denmark, June 21-24, 1992. ACM 1992, ISBN 0-89791-523-2
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