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Web Document Modeling

  • Chapter
The Adaptive Web

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4321))

Abstract

A very common issue of adaptive Web-Based systems is the modeling of documents. Such documents represent domain-specific information for a number of purposes. Application areas such as Information Search, Focused Crawling and Content Adaptation (among many others) benefit from several techniques and approaches to model documents effectively. For example, a document usually needs preliminary processing in order to obtain the relevant information in an effective and useful format, so as to be automatically processed by the system. The objective of this chapter is to support other chapters, providing a basic overview of the most common and useful techniques and approaches related with document modeling. This chapter describes high-level techniques to model Web documents, such as the Vector Space Model and a number of AI approaches, such as Semantic Networks, Neural Networks and Bayesian Networks. This chapter is not meant to act as a substitute of more comprehensive discussions about the topics presented. Rather, it provides a brief and informal introduction to the main concepts of document modeling, also focusing on the systems that are presented in the rest of the book as concrete examples of the related concepts.

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  1. Department of Computer Science and Automation, Artificial Intelligence Laboratory, Roma Tre University, Via della Vasca Navale, 79 - 00146 Rome, Italy

    Alessandro Micarelli, Filippo Sciarrone & Mauro Marinilli

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  1. Alessandro Micarelli
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  2. Filippo Sciarrone
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  3. Mauro Marinilli
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Peter Brusilovsky Alfred Kobsa Wolfgang Nejdl

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Micarelli, A., Sciarrone, F., Marinilli, M. (2007). Web Document Modeling. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds) The Adaptive Web. Lecture Notes in Computer Science, vol 4321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72079-9_5

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