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- W2139320472 abstract "This paper discusses the notion of Uncertainty, which has a prominent place in the theory and experimental practice of modern Physics. It argues that the awareness of Uncertainty may also be of tremendous importance to the eld of Information Retrieval, and in particular Text Categorization. As an application of Uncertainty in Text Categorization, a new criterion for Term Selection is described, which is based on the Uncertainty in Term Frequency across categories. This criterion allows to distinguish between lowquality (or noisy) and high-quality (sti) terms. We describe an experiment investigating the eect of eliminating noisy and sti terms in the context of text classication. In the experiment we applied the Rocchio and Winnow classication algorithms to a collection of newspaper items, a mono-classied subset of the well-known Reuters 21578 corpus. This investigation shows that both the local elimination of noisy terms and the global elimination of sti terms can be used for Term Selection in Text Categorization." @default.
- W2139320472 created "2016-06-24" @default.
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- W2139320472 date "2002-01-01" @default.
- W2139320472 modified "2023-09-26" @default.
- W2139320472 title "MANAGEMENT OF UNCERTAINTY AND IMPRECISION IN MULTIMEDIA INFORMATION SYSTEMS: INTRODUCING THIS SPECIAL ISSUE" @default.
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