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Document Correlation Measurement based on Conceptual Dependent Forest

Volume 14, Number 6, June 2018, pp. 10991108
DOI: 10.23940/ijpe.18.06.p1.10991108

Gang Liu, Hanwen Zhang, and Hanmo Zhang

School of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, China

(Submitted on March 1, 2018; Revised on April 21, 2018; Accepted on May 15, 2018)


The formal expression of natural language is the primary task of all natural language problems. In this paper, we propose the concept of conceptual dependency tree based on the conceptual dependency theory. Conceptual dependency differs from dependency analysis in that the performance at the grammatical and semantic level is more concerned with the conceptual hierarchy. Based on the conceptual dependency tree, a conceptual dependency forest model is defined, which provides a solution to the formalized representation of natural language. Based on the conceptual dependency forest model, the definition and calculation method of conceptual dependency strength and potential similarity are further proposed. The experiment proves that the conceptual dependency forest model proposed in this paper is reasonable and effective.


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