Combining content-based and context-based methods for Persian web page classification

As the Internet includes millions of web pages for each and every search query, a fast retrieving of the desired and related information from the Web becomes very challenging subject. Automatic classification of web pages into relevant categories is an important and effective way to deal with the difficulty of retrieving information from the Internet. 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. We conduct various experiments on a dataset consisting of 352 pages belonging to Persian Wikipedia, using content-based and context-based web page features. Our experiments demonstrate the usefulness of combining these features.