Venn diagram-based feature ranking technique for key term extraction

Abstract

Classification of text documents from a pool of huge collection of the same is performed usually on the basis of certain key terms present in the said documents that distinguish a particular document set from the universal set. Generally, these key terms are identified using some feature sets, which can be statistical, rule-based, linguistic, or hybrid in nature. This paper develops a simple technique based on Venn diagram to prioritize the different standard features available in the literature, which in turn reduces the dimension of the feature sets used for document classification.