Abstract:

Webpage classification is an important concept nowadays. The increases of the internet web users require a manageable tool for classifying the huge amount of information available in the webpages. For this purpose, the paper proposes a webpage trainer and classifier (SENclassifier) that uses the semantic expansion network (SEN) along with the Spreading Activation Model (SA), SENclassifier considers the relationships between terms not like other classifiers depend only on the statistical (frequency) value of each term.