Feature Selection Method Based on Domain-specific Term Extraction
The traditional text representation methods for text classification are generally based on the analysis of full text (Bag-of-Words). Because of ignoring domain-specific semantic features, they can not fit domain-specific text classification. This paper describes a feature selection method based on domain-specific term extraction using corpus comparison, and a text classification system based on the combination of this method and the SVM classifier, which can be applied to any domain easily. This text classification system got the highest score among runs from 19 groups in the evaluation of TREC 2005 Genomics Track Categorization Task.