Abstract
Nowadays, the Web is an essential tool for most people. Internet provides millions of web pages for each and every search term. The Internet is a powerful medium for communication between computers and accessing online documents but it is not a tool for locating or organizing information. Tools like search engines assist users in locating information. The amount of daily searches on the web is broad and the task of getting interesting and required results quickly becomes very difficult. The use of an automatic web page classifier can simplify the process by assisting the search engine in getting relevant results. The web pages can present different and varied information depending on the characteristics of its content. The uncontrolled nature of web content presents additional challenges to web page classification as compared to traditional text classification, but the interconnected nature of hypertext also provides features that can assist the process. This paper analyses the feasibility of an automatic web page classifier, proposes several classifiers and studies their precision. In this sense, Data Mining techniques are of great importance and will be used to construct the classifiers.
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Fiol-Roig, G., Miró-Julià, M., Herraiz, E. (2011). Data Mining Techniques for Web Page Classification. In: Pérez, J.B., et al. Highlights in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, vol 89. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19917-2_8
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DOI: https://doi.org/10.1007/978-3-642-19917-2_8
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