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A Web Metadata Based-Model for Information Quality Prediction

A Web Metadata Based-Model for Information Quality Prediction

Ricardo Barros, Geraldo Xexéo, Wallace A. Pinheiro, Jano de Souza
Copyright: © 2008 |Pages: 20
ISBN13: 9781599048475|ISBN10: 1599048477|EISBN13: 9781599048482
DOI: 10.4018/978-1-59904-847-5.ch019
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MLA

Barros, Ricardo, et al. "A Web Metadata Based-Model for Information Quality Prediction." Handbook of Research on Web Information Systems Quality, edited by Coral Calero, et al., IGI Global, 2008, pp. 324-343. https://doi.org/10.4018/978-1-59904-847-5.ch019

APA

Barros, R., Xexéo, G., Pinheiro, W. A., & de Souza, J. (2008). A Web Metadata Based-Model for Information Quality Prediction. In C. Calero, M. Angeles Moraga, & M. Piattini (Eds.), Handbook of Research on Web Information Systems Quality (pp. 324-343). IGI Global. https://doi.org/10.4018/978-1-59904-847-5.ch019

Chicago

Barros, Ricardo, et al. "A Web Metadata Based-Model for Information Quality Prediction." In Handbook of Research on Web Information Systems Quality, edited by Coral Calero, M. Angeles Moraga, and Mario Piattini, 324-343. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-847-5.ch019

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Abstract

Currently, in the Web environment, users have to deal with an enormous amount of information. In a Web search, they often receive useless, replicated, outdated, or false data, which, at first, they have no means to assess. Web search engines provide good examples of these problems: As reply from these mechanisms, users usually find links to replicated or conflicting information. Further, in these cases, information is spread out among heterogeneous and unrelated data sources, that normally present different information quality approaches. This chapter addresses those issues by proposing a Web Metadata-Based Model to evaluate and recommend Web pages based on their information quality, as predicted by their metadata. We adopt a fuzzy theory approach to obtain the values of quality dimensions from metadata values and to evaluate the quality of information, taking advantage of fuzzy logic’s ability to capture humans’ imprecise knowledge and deal with different concepts.

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