Web Content Filtering

Web Content Filtering

Elisa Bertino (Purdue University, USA), Elena Ferrari (University of Insubria at Como, Italy) and Andrea Perego (University of Milan, Italy)
Copyright: © 2006 |Pages: 21
DOI: 10.4018/978-1-59140-588-7.ch006
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Abstract

The need to filter online information in order to protect users from possible harmful content can be considered as one of the most compelling social issues derived from the transformation of the Web into a public information space. Despite that Web rating and filtering systems have been developed and made publicly available quite early, no effective approach has been established so far, due to the inadequacy of the proposed solutions. Web filtering is then a challenging research area, needing the definition and enforcement of new strategies, considering both the current limitations and the future developments of Web technologies—in particular, the upcoming Semantic Web. In this chapter, we provide an overview of how Web filtering issues have been addressed by the available systems, bringing in relief both their advantages and shortcomings, and outlining future trends. As an example of how a more accurate and flexible filtering can be enforced, we devote the second part of this chapter to describing a multi-strategy approach, of which the main characteristics are the integration of both list- and metadata-based techniques and the adoption of sophisticated metadata schemes (e.g., conceptual hierarchies and ontologies) for describing both users’ characteristics and Web pages content.

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