Automatic indexing based on Bayesian inference networks

  • Authors:
  • Kostas Tzeras;Stephan Hartmann

  • Affiliations:
  • -;-

  • Venue:
  • SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
  • Year:
  • 1993

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Abstract

In this paper, a Bayesian inference network model for automatic indexing with index terms (descriptors) from a prescribed vocabulary is presented. It requires an indexing dictionary with rules mapping terms of the respective subject field onto descriptors and inverted lists for terms occuring in a set of documents of the subject field and descriptors manually assigned to these documents. The indexing dictionary can be derived automatically from a set of manually indexed documents. An application of the network model is described, followed by an indexing example and some experimental results about the indexing performance of the network model.