Text Categorization Based on Domain Ontology

Methods based on machine learning have been proposed with certain advantages for TC (text categorization). However, it is still difficult to further increase the precision and understandability of categorization due to certain aspects of text itself. In this paper, we propose an architecture for TC by addressing domain ontology. Not only more effect and understandability of categorization are achieved, simulation results show a great reducing of keyword numbers and saving of system costs.