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Type-2 fuzzy description logic

ISSN号：1673-7350
期刊名称：Frontiers of Computer Science in China
时间：0
页码：205-215
语言：英文
分类：TP18[自动化与计算机技术—控制科学与工程;自动化与计算机技术—控制理论与控制工程] TP273[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
作者机构：[1]Intelligent and Distributed Computing Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology Wuhan 430074, China, [2]State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China
相关基金：Acknowledgements This work was supported by the National Natural Science Foundation of China （Grant Nos. 60873225, 60873083, and 70771043）, the National High Technology Research and Development Program of China （2007AA01Z403）, the Natural Science Foundation of Hubei Province （2009CDB298）, the Natural Science Foundation of Hubei Province for Distinguished Young Scholars （2008CDB351）, the Wuhan Youth Science and Technology Chenguang Program （200950431171）, the Open Foundation of State Key Laboratory of Software Engineering （SKLSE20080718）, the Innovation Fund of Huazhong University of Science and Technology （2010MS068, Q2009021）.
相关项目：基于链接挖掘的动态金融网络分析技术研究

关键词：描述逻辑, 模糊, 2型, WEB本体语言, WEB应用系统, 推理算法, 知识表示, ALC, description logic （DL）, type-2 fuzzy attributive concept language with complements （ALC）, fuzzy ontology, reasoning, semantic search engine

中文摘要：

描述逻辑(DL ) 广泛地在最近的语义网应用程序系统被采用。然而，当处理不精确的概念和角色时，古典描述逻辑被限制，因此为这个工作提供动机。在这份报纸，我们在场 type-2 有补充(ALC ) 的模糊归属的概念语言并且提供它的知识表示和推理算法。我们也建议 type-2 模糊的网本体论语言(猫头鹰) 到基于 type-2 造模糊本体论模糊 ALC 和分析推理算法的稳固，完全性，和复杂性。把模糊 ALC 比作 type-1，模糊 ALC 能描述的 type-2 不精确的知识更细致地由使用会员度间隔。我们基于 type-2 实现一个语义搜索引擎模糊 ALC 并且在真实数据上执行实验测试它的性能。结果证明模糊 ALC 能改进的 type-2 为不精确的信息的相关点击的数字寻找的精确和增加。

英文摘要：

Description logics （DLs） are widely employed in recent semantic web application systems. However, classical description logics are limited when dealing with imprecise concepts and roles, thus providing the motivation for this work. In this paper, we present a type-2 fuzzy attributive concept language with complements （ALC） and provide its knowledge representation and reasoning algorithms. We also propose type-2 fuzzy web ontology language （OWL） to build a fuzzy ontology based on type- 2 fuzzy ALC and analyze the soundness, completeness, and complexity of the reasoning algorithms. Compared to type-1 fuzzy ALC, type-2 fuzzy ALC can describe imprecise knowledge more meticulously by using the membership degree interval. We implement a semantic search engine based on type-2 fuzzy ALC and carry out experiments on real data to test its performance. The results show that the type-2 fuzzy ALC can improve the precision and increase the number of relevant hits for imprecise information searches.

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