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.
CITATION STYLE
Chakraborty, N., Mukherjee, S., Naskar, A. R., Malakar, S., Sarkar, R., & Nasipuri, M. (2017). Venn diagram-based feature ranking technique for key term extraction. In Advances in Intelligent Systems and Computing (Vol. 515, pp. 333–341). Springer Verlag. https://doi.org/10.1007/978-981-10-3153-3_33
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