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| Network-Based Analysis for Discovering Semantic Redundancy |
| WANG Guodong, GAO Chao, YUAN Ye, ZHANG Zili
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| a.School of Computer and Information Science; b.Key Laboratory of Intelligent Software and Software Engineering, Southwest University, Chongqing 400715, China |
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Abstract The efficiency of semantic reasoning can be improved through constructing the semantic ontology reasonably and reducing the redundant information in the process of reasoning. It is a feasible method to reveal the reason of the redundant information in the process of reasoning through analyzing the dynamic changes of an ontology structure and the important role of nodes in an ontology. Taking AGROVOC ontology network as an example, this paper provides qualitative analyses based on the reasoning mechanism of semantic web for understanding the redundant information. Meanwhile, some quantitative measurements from the perspective of complex network are provided in order to identify the core concepts in a semantic web, and further to solve the problem of redundant information. Experimental results show that the reasoning of semantic web and the rationality of ontology construction can be quantitatively analyzed from the perspective of complex network, which provides a new measurement to optimize the design of ontology and improve the efficiency of reasoning in the semantic web.
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Received: 04 June 2015
Published: 24 February 2025
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