摘要
随着互联网上数据的增长,如何更有效地利用数据成为了一个亟待人们解决的问题。为此语义网被提出,使得机器可以帮助人们处理这些数据。语义网的核心是本体,因此语义网的发展和人们对互联网上信息的本体构建相关。如何快速准确地构建本体是语义网发展的关键。构建语义本体本身又是一件繁琐的工作,当今的本体学习技术利用机器学习和数据挖掘的技术来实现本体的自动或半自动构建。文中将双聚类算法的思想引入到本体构建当中,同时提出了FIU-CTWC双聚类算法,解决了一维聚类不能聚出多重语义的问题。
As the amount of data in the Internet become more and more large, how to use the data more effectively turn into a problem which need people to solve. At this background, the semantic web was provided. Using semantic web computer can help people to handle the data. The development of semantic web largely depends on the number of ontology in the Internet. How to construct ontology quickly and precisely is the key of the semantic web＇s development. Ontology learning aims to construct the ontology automatically or semi-automatically with the help of techniques like machine learning and data mining. It uses a refine biclustering algorithms FIU-CTWC to con- struct the ontology in order to overcome the shortage of 1 D clustering algorithms.
出处
《计算机技术与发展》
2013年第3期27-30,共4页
Computer Technology and Development
基金
国家自然科学基金资助项目(60971088)
江苏省高校"青蓝工程"中青年学术带头人培养对象资助项目
关键词
双聚类
本体自动构建
语义网
biclustering algorithms
ontology auto construction
semantic web
