Title: Building course semantic view for representing course content concisely

Authors: Shunxiang Zhang; Yin Wang; Shiyao Zhang; Guangli Zhu

Addresses: School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, China ' School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, China ' School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, China ' School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, China

Abstract: Concise semantic representation of a course can help students conveniently master the entire content of a course. Also, it can provide technology support for semantic searching of courses for some online systems such as e-learning system, and e-book market recommendation system. The main task of course semantic representation is how to concisely and completely represent the course content. This paper proposes a semantic representation method for Chinese courses. First, to concisely represent the course semantic, some course professional terms with hyponymy relation are zoomed (or merged) into a term. Second, association semantic existing in professional terms of a course is mined to represent course semantic (i.e., course knowledge). Finally, based on the condensed professional terms and the mined association semantic, course semantic view is built to make the course semantic more intuitive and visual. The experimental results show that the proposed model can represent courses semantics well.

Keywords: semantic representation; professional terms; hyponymy relation; association semantics; course semantic view; course content; e-learning; electronic learning; online learning; e-books; recommendation systems; recommender systems; computer science education; data mining.

DOI: 10.1504/IJCSE.2016.080222

International Journal of Computational Science and Engineering, 2016 Vol.13 No.4, pp.400 - 409

Received: 06 Feb 2016
Accepted: 03 Mar 2016

Published online: 04 Nov 2016 *

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