Network-Based Analysis for Discovering Semantic Redundancy
WANG Guodong, GAO Chao, YUAN Ye, ZHANG Zili
a.School of Computer and Information Science; b.Key Laboratory of Intelligent Software and Software Engineering, Southwest University, Chongqing 400715, China
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.
[1] Meenachi N, Sai Baba M. Web ontology language editors for semantic web: a survey[J].International Journal of Computer Applications, 2012, 53(12): 12-16. [2] Antoniou G, Van Harmelen F. A semantic web primer[M].Cambridge, Massachusetts, United States: MIT Press, 2004: 9-12. [3] Berners-Lee T, Hendler J, Lassila O. The semantic web[J].Scientific American, 2001, 284(5): 28-37. [4] Yuan Y, Zeng W, Zhang Z L. A semantic technology supported precision agriculture system: a case study for citrus fertilizing[C]//6th International Conference on Knowledge Science, Engineering and Management. Dalian, China: Springer Berlin Heidelberg, 2013: 104-111. [5] The AGROVOC team. AGROVOC[OL].(2015-03-01)[2015-06-01].http://aims.fao.org/zh-hans/agrovoc. [6] 王艺, 王英, 原野,等. 基于语义本体的柑橘肥水管理决策支持系统[J].农业工程学报, 2014, 30(9): 93-101. Wang Yi, Wang Ying, Yuan Ye, et al. A decision support system for fertilization and irrigation management of citrus based on semantic ontology[J].Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(9): 93-101. [7] Xu Y, Zou S, Gu A, et al. Research on the complex network of the UNSPSC ontology[J].Physics Procedia, 2012, 24: 1863-1867. [8] eh I, Zorman M, repinek M, et al. Ontop: A Component for Acquiring Information from OWL Ontologies[J].Acta Electrotechnica et Informatica, 2012, 12(1): 30-37. [9] Zhang H, Li Y F, Tan H B K. Measuring design complexity of semantic web ontologies[J].Journal of Systems and Software, 2010, 83(5): 803-814. [10] Hsi I. Analyzing the conceptual coherence of computing applications through ontological excavation[D].Atlanta: Georgia Institute of Technology, 2004. [11] Caracciolo C, Stellato A, Morshed A, et al. The agrovoc linked dataset[J].Semantic Web, 2013, 4(3): 341-348. [12] Rajbhandari S, Keizer J. The AGROVOC concept scheme-a walkthrough[J].Journal of Integrative Agriculture, 2012, 11(5): 694-699. [13] Manaf N A A, Bechhofer S, Stevens R. The current state of SKOS vocabularies on the web[C]//9th Extended Semantic Web Conference. Greece: Springer Berlin Heidelberg, 2012: 270-284. [14] Myers T, Atkinson I. Eco-informatics modelling via semantic inference[J].Information Systems, 2013, 38(1): 16-32. [15] 唐晋韬, 王挺, 王戟. 利用复杂网络分析方法研究基因本体隐藏结构信息[J].东南大学学报:英文版, 2010, 1: 31-35. Tang JinTao, Wang Ting, Wang Ji. Discovering hidden information of gene ontology based on complex networks analysis[J].Journal of Southeast University, 2010, 26(1): 31-35. [16] 张自力,李莉.语义万维网——工程实践指南[M].第2版.北京:高等教育出版社,2015:184-185. [17] 张大陆, 王志晓, 刘雯,等. 基于复杂网络的本体结构分析[J].同济大学学报: 自然科学版, 2009, 2: 258-261. Zhang Da, Wang Zhixiao, Liu Wen, et al. Complex network-based ontology structure analysis[J].Journal of Tongji University (Natural Science), 2009, 2: 258-261. [18] Costa L F, Oliveira Jr O N, Travieso G, et al. Analyzing and modeling real-world phenomena with complex networks: a survey of applications[J].Advances in Physics, 2011, 60(3): 329-412. [19] Maoz Z. Preferential attachment, homophily, and the structure of international networks, 1816-2003[J].Conflict Management and Peace Science, 2012, 29(3): 341-369. [20] Zhou L, Lu F, Zhang H. Evaluating road selectivity of urban-trip based on dynamic betweenness centrality[C]//The 20th International Conference on Geoinformatics (GEOINFORMATICS). Hong Kong: IEEE, 2012: 1-5. [21] Gulati R, Sytch M, Tatarynowicz A. The rise and fall of small worlds: Exploring the dynamics of social structure[J].Organization Science, 2012, 23(2): 449-471. [22] 周漩, 张凤鸣, 李克武,等. 利用重要度评价矩阵确定复杂网络关键节点[J].物理学报, 2012, 61(5): 050201. Zhou Xuan, Zhang Fengming, Li Kewu, et al. Use importance evaluation matrix to determine the complex network nodes[J].Journal of Physics, 2012, 61(5): 050201. [23] 任晓龙,吕琳媛. 网络重要节点排序方法综述[J].科学通报, 2014, 13: 1175-1197. Ren Xiaolong, Lv Linyuan. Review of ranking nodes in complex networks[J].Chinese Science Bulletin, 2014, 13: 1175-1197. [24] Zhang X, Cheng G, Ge W Y, et al. Summarizing vocabularies in the global semantic web[J].Journal of Computer Science and Technology, 2009, 24(1): 165-174.
