Abstract
Classical approaches, namely term weighting and statistical document clustering do not score to achieve substantial breakthroughs in information retrieval research. Information retrieval systems must be designed to overcome the syntactical barrier in document representation. This paper discusses the combination of classical term weighting approaches and probabilistic inference concepts to form a powerful semantic document classification model. BRANT is a prototype adapting inference strategies from medical differential diagnosis to the area of information retrieval.
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© 1992 Springer-Verlag/Wien
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Merkl, D., Min Tjoa, A., Vieweg, S. (1992). BRANT — An Approach for Knowledge Based Document Classification in the Information Retrieval Domain. In: Tjoa, A., Ramos, I. (eds) Database and Expert Systems Applications. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7557-6_44
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DOI: https://doi.org/10.1007/978-3-7091-7557-6_44
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82400-9
Online ISBN: 978-3-7091-7557-6
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