Venn diagram-based feature ranking technique for key term extraction

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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.

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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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