Abstract
The paper considers the problem of improving the quality of web sites categorization using data mining methods. This goal is important for automated systems of parental control. The purpose of such systems is protection from unwanted or inappropriate information. The novelty of the proposed approach is in usage of HTML tags statistics of web pages to improve the categorization of sites that are similar in terms of textual content, but differing in their structural features. The paper describes the architecture of the categorization system, the algorithm of its work, the results of experiments, and assessment of classification quality.
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Acknowledgment
This research is being supported by The Ministry of Education and Science of The Russian Federation (contract # 14.604.21.0147, unique contract identifier RFMEFI60414X0147).
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Novozhilov, D., Kotenko, I., Chechulin, A. (2016). Improving the Categorization of Web Sites by Analysis of Html-Tags Statistics to Block Inappropriate Content. In: Novais, P., Camacho, D., Analide, C., El Fallah Seghrouchni, A., Badica, C. (eds) Intelligent Distributed Computing IX. Studies in Computational Intelligence, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-25017-5_24
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DOI: https://doi.org/10.1007/978-3-319-25017-5_24
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