A Combination based on OWA Operators for Multi-label Genre Classification of web pages

This paper presents a new method for genre identification that combines homogeneous classifiers using OWA (Ordered Weighted Averaging) operators. Our method uses character n-grams extracted from different information sources such as URL, title, headings and anchors. To deal with the complexity of web pages, we applied MLKNN as a multi-label classifier, in which a web page can be affected by more than one genre. Experiments conducted using a known multi-label corpus show that our method achieves good results.