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基于FCA与统计学习的本体生成技术研究

The Research of Ontology Establishing Technology Base on FCA and Statistics

【作者】 闫瑞海

【导师】 田宏;

【作者基本信息】 大连交通大学 , 计算机应用技术, 2010, 硕士

【摘要】 20世纪90年代以来,信息科学的发展面临着种种新的难题,主要包括知识表示、信息组织、软件利用等。特别是由于因特网的快速发展,如何组织、管理和维护大量信息并为用户提供有效的服务也就成为一项重要而迫切的研究任务。为适应这些要求,哲学领域的本体被引入信息科学领域,由于国内外众多学者的研究,已经发展成为能在语义和知识层次上描述信息系统的概念模型建模工具,并在信息检索、信息抽取、异构信息系统的互操作和集成、语义Web等领域得到了广泛应用。本文主要围绕本体生成技术及本体的优化方法进行展开。论文在分析当前经典本体生成方法的基础上,提出了基于FCA与统计学习相结合的本体生成算法,提出了在应用FCA相关理论生成概念格时的四个统计量,构造了基于FCA与统计学习相结合生成的概念格到本体的映射过程;基于FCA中概念格的现有理论,特别是继承概念格理论,得出有关冗余概念的推论和优化概念格的定义,从而形成了本体优化算法的基础;论文还对本体迁移学习进行了研究。通过以上本体生成及优化过程,能够得到比较理想的本体结构。最后本文给出了本体生成的框架模型和可视化本体生成平台。通过本文提出的本体生成技术与方法,能够准确地提取领域知识,建立结构清晰、重点突出的领域知识本体,对于有效组织、管理和维护大量信息,有效地从大量信息中提取关键知识具有重要意义。

【Abstract】 Since the 1990s, the development of information science is facing many new problems, mainly, such as knowledge representation, information organization, and software utilization. Particularly because of the rapid development of the Internet, how to organize, manage and maintain a amount of information and provide users with efficient service has become an important and urgent research content. To meet these requirements, ontology, a concept from the field of philosophy, is introduced to the field of information science, due to a number of researches, it has become a concept modeling tools which can describe information systems on the semantic and knowledge levels, and has been widely used in information retrieval, information extraction, heterogeneous information systems interoperability and integration, Semantic Web and other applications.This paper mainly focuses on generating technologies of ontology construction and ontology optimization method. Paper represents a detailed analysis of the current classical ontology generation methods, with analyzing their strengths and weakness, paper gives the ontology generation algorithms base on the combination of the proposed FCA and statistical learning. Proposes four statistics in the construction of concept lattice and construct mapping process from concept lattice to ontology. In addition, base on the existing theory of FCA concept lattice, in particular, inheritance concept lattice theory, paper draws inferences about the concept of redundancy and the definition of optimizing concept lattice, thus forming the basis of ontology optimization algorithm, and gives a research of similar ontology conducting. Through the above process Ontology, a more ideal ontology structure can be got with ontology generation and optimization. Finally, this paper gives a framework of generating ontology and generates the interface for visualization of ontology construction.Through the ontology constructing techniques and methods of this paper, which can accurately extract the domain knowledge, and establish a clear and focused domain knowledge ontology, which has great significance to effectively organize, manage, maintain a large amount of information and extract critical knowledge from a large number of information.

【关键词】 本体概念格统计学习统计优化
【Key words】 OntologyConcept latticeStatistical LearningStatisticsOptimization
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