基于数据挖掘的语义web系统设计与实现

发布时间：2018-03-01 11:25

本文关键词： 语义Web 本体数据挖掘 Apriori算法　出处：《电子科技大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着互联网络的飞速发展,互联网络涉及到了新闻、政府、教育、广告等社会各个方面。Internet应用的普及使得数据挖掘技术的重点已经从传统的基于数据库的应用转移到了基于Web的应用。在信息技术的推动下,Web已经成为了社会上信息生产、加工、发布和处理的主要凭条,Web上的数据正在呈爆炸式增长,为了帮助用户在海量的Web数据中迅速找到有用的信息,从Web服务和文档中发现有用信息的数据挖掘也成为了当前研究的重点。Web挖掘就是从互联网络上的Web文档中抽取隐藏的信息和模式,但是Web海量的数据大多都是非结构化或者半结构化的,因此利用传统的数据挖掘技术来挖掘web上有用信息的效果不佳。语义Web是现有Web的扩展,并且使得Web不仅仅是一种信息展示的平台,同时也有助于计算机理解Web上的内容。本文一方面,对如何在Web上提取新的语义本体结构来发展Web挖掘进行了研究;另一方面,如何针对所研究的语义网结构在Web挖掘中的应用进行了实例验证。针对语义Web的数据挖掘研究所做的具体工作如下:首先,针对语义Web的研究,主要采用Protégé工具对如何创建本体,以及如何往本体中添加实例和属性。其次,利用成熟的Apriori关联规则数据挖掘算法对已经创建,且添加了实例的本体进行数据挖掘,从而获得其中新的知识。最后,在结果分析方面,借助java开发工具包中的Jena工具局,利用其推理功能,对已经建立的语义Web进行推理,并且将所得到的新的推理规则与本文所研究的语义Web系统中获得的知识进行对比。本文所研究得到的推理规则,放到推理规则库中,用于语义Web库的扩展,实现本体提取的半自动化,并且最大程度的获取网络无规则数据中的新知识,不仅可以较好的克服传统Web所存在的一些缺陷,同时也有利于提高网络上信息的利用效率。
[Abstract]:With the rapid development of the Internet, the Internet involves news, government, education, With the popularity of Internet applications, the emphasis of data mining technology has shifted from the traditional database based application to the Web based application. With the promotion of information technology, web has become the information production and processing in the society. Data published and processed primarily on Web is exploding in order to help users quickly find useful information in a vast amount of Web data. Discovery of useful information from Web services and documents has also become the focus of current research. Web mining is extracting hidden information and patterns from Web documents on the Internet. However, the mass data of Web is mostly unstructured or semi-structured, so it is not effective to mine useful information on web by using traditional data mining technology. Semantic Web is an extension of existing Web. Web is not only a platform for information display, but also helpful for computer to understand the content of Web. On the one hand, this paper studies how to extract new semantic ontology structure from Web to develop Web mining; on the other hand, How to validate the application of semantic web structure in Web mining. The research work of semantic Web data mining is as follows: first, the research on semantic Web. It mainly uses Prot 茅 g 茅 tool to create ontology, and how to add instances and attributes to ontology. Secondly, it uses mature Apriori association rule data mining algorithm to mine the ontology that has been created and has added instances. Finally, in the aspect of result analysis, with the help of the Jena tool bureau in the java development toolkit, the reasoning function is used to infer the established semantic Web. The new reasoning rules obtained in this paper are compared with the knowledge gained in the semantic Web system studied in this paper. The reasoning rules obtained in this paper are put into the inference rule base for the extension of the semantic Web library. To realize the semi-automation of ontology extraction and to obtain the new knowledge in the non-regular data of the network to the greatest extent can not only overcome some defects of the traditional Web, but also improve the efficiency of information utilization on the network.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.09;TP311.52

【参考文献】