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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Text and Hypertext Categorization
verfasst von : Houda Benbrahim, Max Bramer
Erschienen in: Artificial Intelligence An International Perspective
Verlag: Springer Berlin Heidelberg
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Automatic categorization of text documents has become an important area of research in the last two decades, with features that make it significantly more difficult than the traditional classification tasks studied in machine learning. A more recent development is the need to classify hypertext documents, most notably web pages. These have features that add further complexity to the categorization task but also offer the possibility of using information that is not available in standard text classification, such as metadata and the content of the web pages that point to and are pointed at by a web page of interest. This chapter surveys the state of the art in text categorization and hypertext categorization, focussing particularly on issues of representation that differentiate them from ’conventional’ classification tasks and from each other.