Machine Learning Algorithms in Web Page Classification

The contemporary world is heavily influenced by web technology, with a significant increase in web information every year. Manual classification of web page documents proves to be both time-consuming and inaccurate, given the abundance of irrelevant, redundant, and noisy information present in web pages. Therefore, an automatic web page classification system becomes essential. Web page classification plays a crucial role in information management and retrieval tasks. Feature selection is a pivotal step in achieving accurate web page classification.Web pages typically contain a large number of features, which can adversely affect classification accuracy. The primary objective of the proposed research is to develop a hybrid feature selection approach that is not only efficient but also effective in automatically classifying web pages. This approach not only enhances classification accuracy but also aids web search tools in delivering relevant results within the appropriate category.

Autorentext

Dr. S. Markkandeyan and Dr. A. Dennis Ananth are currently working as Senior Assistant Professors, School of Computing at SASTRA Deemed University, Thanjavur, Tamil Nadu, India.Dr. M. Rajakumaran and Dr. R. Venkatesan are currently working as Assistant Professors III, School of Computing at SASTRA Deemed University, Thanjavur, Tamilnadu, India.