Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Centroid-Based Document Classification: Analysis and Experimental Results
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Multi-label Classification Using Ensembles of Pruned Sets
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
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This paper proposes an improved centroid-based approach to classify web pages by genre using character n-grams extracted from URL, title, headings and anchors. To deal with the complexity of web pages and the rapid evolution of web genres, our approach implements a multi-label and incremental scheme in which web pages are classified one by one and can be affected to more than one genre. According to the similarity between the new page and each genre centroid, our approach either adjust the genre centroid or considers the new page as noise page and discards it. Conducted experiments show that our approach is very fast and achieves superior results over existing multi-label classifiers.