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Text and Hypertext Categorization

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Artificial Intelligence An International Perspective

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5640))

Abstract

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.

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  1. Ernst and Young LLP, 1 More London Place, London, SE1 2AF, United Kingdom

    Houda Benbrahim

  2. School of Computing, University of Portsmouth, Portsmouth, Hants, PO1 3HE, United Kingdom

    Max Bramer

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  1. Houda Benbrahim
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  1. School of Computing, Lion Terrace, University of Portsmouth, PO1 3HE, Portsmouth, Hants, UK

    Max Bramer

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Benbrahim, H., Bramer, M. (2009). Text and Hypertext Categorization. In: Bramer, M. (eds) Artificial Intelligence An International Perspective. Lecture Notes in Computer Science(), vol 5640. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03226-4_2

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