A Hybrid Mechanism for Auto Text Categorization in Web Documents

Web personalization has become such a popular paradigm nowadays, that almost all e-commerce websites are including it in their websites. The main objective of web is driven by grouping similar pages. text categorization principle becomes challenge when daily users visit numerous This paper develops hybrid framework which categorizes the extracted from document, applying Neighbourhood Preserving Embedding algorithm and then Particle Swarm Optimization on groups, resulting into group documents contain texts. proposed mechanism relatively high performance improves with time, as size increase, particle swarm also evolves its nature.