Design and Implementation of Hybrid Algorithm for e-news Classification. - Kaur, Harneet; Jyoti, Kiran (INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, 2013)
Data mining involves the use of data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. As the use of internet is increasing day by day and with the advancement of internet news also publish online. So to handle this bulk amount of news various data mining techniques for classification had been used. In this paper we are using an intelligent system based on Hybrid algorithm (HMM, SVM and CART) for e-news classification. An intelligent system is designed which will extract the online news and then will find out category and subcategory wise news. System involves four main stages: a) Keyword Extraction b) Implementation of Hybrid Algorithm (HMM, SVM and CART). Data have been collected for experimentation from online newspapers like The Hindu, Hindustan Times and Times of India. The experimental results are based on the news categories and sub categories such as Entertainment: Bollywood 100% and Hollywood 90%, Sports: Cricket 90%, Football 90% and Hockey 78%, Matrimonial :Hindu 100% and Muslim 80%. In this paper we also compare the result of Hybrid algorithm (HMM, SVM and CART) with individual HMM and SVM Algorithm and conclude that Hybrid algorithm (HMM, SVM and CART) gave better result than that of what HMM and SVM individually gave.