A Persian Web Page Classifier Applying a Combination of Content-Based and Context-Based Features
|A Persian Web Page Classifier Applying a Combination of Content-Based and Context-Based Features|
|Author(s)||M. Farhoodi, A. Yari, M. Mahmoudi|
|Published in||International Journal of Information Studies|
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A Persian Web Page Classifier Applying a Combination of Content-Based and Context-Based Features is a 2009 journal article written in English by M. Farhoodi, A. Yari, M. Mahmoudi and published in International Journal of Information Studies.
There are many automatic classification methods and algorithms that have been propose for content-based or context-based features of web pages. In this paper we analyze these features and try to exploit a combination of features to improve categorization accuracy of Persian web page classification. In this work we have suggested a linear combination of different features and adjusting the optimum weighing during application. To show the outcome of this approach, we have conducted various experiments on a dataset consisting of all pages belonging to Persian Wikipedia in the field of computer. These experiments demonstrate the usefulness of using content-based and context-based web page features in a linear weighted combination.
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