Current Proceedings on Technology

Yazarlar: Selma Ayse Ozel, Esra Sarac

Konular:-

Anahtar Kelimeler:Intelligent Water Drops,Web page classification,Classification,Feature selection  

Özet:   Increase in the amount of information on the Web has caused the need for accurate automated classifiers for Web pages to maintain Web directories and to increase search engines’ performance. As every (HTML/XML) tag and every term on each Web page can be considered as a feature, we need efficient methods to select best features to reduce feature space of the Web page classification problem. In this study, our aim is to apply a recent optimization technique namely the Intelligent Water Drops (IWD) algorithm, to select best features for Web page classification problem. IWD is a swarm based optimization algorithm which has been inspired from natural water drops in rivers. In this study, we use IWD to select a subset of features, and to evaluate the fitness of the selected features J48 classifier of the Weka data mining tool is employed. WebKB and Conference datasets were used to evaluate the effectiveness of the proposed feature selection system. We observed that when a subset of features are selected by using IWD, WebKB and Conference datasets were classified without loss of accuracy, even more, time needed to classify new Web pages reduced sharply as the number of features were decreased. 

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