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• W2001738676 abstract "Text mining is about inferring structure from sequences representing natural language text, and may be defined as the process of analyzing text to extract information that is useful for particular purposes. Although hand-crafted heuristics are a common practical approach for extracting information from text, a general, and generalizable, approach requires adaptive techniques. This paper studies the way in which the adaptive techniques used in text compression can be applied to text mining. It develops several examples: extraction of hierarchical phrase structures from text, identification of keyphrases in documents, locating proper names and quantities of interest in a piece of text, text categorization, word segmentation, acronym extraction, and structure recognition. We conclude that compression forms a sound unifying principle that allows many text mining problems to be tacked adaptively." @default.
• W2001738676 created "2016-06-24" @default.
• W2001738676 creator A5034144529 @default.
• W2001738676 date "2004-06-01" @default.
• W2001738676 modified "2023-09-29" @default.
• W2001738676 title "Adaptive text mining: inferring structure from sequences" @default.
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• W2001738676 doi "https://doi.org/10.1016/s1570-8667(03)00084-4" @default.
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