基于Web数据的本体概念抽取  

The Research of Concept Extraction based on Web Data Mining for Ontology Learning

作　　者：强彦[1] 谢红薇[1] 

机构地区：[1]太原理工大学计算机与软件学院,太原030024

出　　处：《电脑开发与应用》2007年第11期37-39,共3页Computer Development & Applications

基　　金：山西省自然科学基金(No.20051035)资助

摘　　要：本体论(Ontology)在知识管理及语义网(Semantic Web)中越来越重要,但建造本体往往需要耗费大量的时间,且建造完成后本体的维护对知识管理者来说也是费时的工作。自动创建领域Ontology可以克服手工方法的不足,成为当前的研究热点之一;而概念是本体中最重要的组成部分之一,从半结构化的Web文档中自动抽取概念的效率和准确度的高低,直接决定了自动建造的本体的质量,提出一种自动的本体概念抽取模型,此模型不依赖于领域词典或核心本体,并且能达到快速有效地通过对中文Web文本挖掘自动地构建及更新领域本体概念的目的。Ontology is increasingly important in knowledge management and Semantic Web. The problem of it is that the construction of ontology is a time-consuming job and ontology engineers also need to spend much time to maintain it. Overcoming the deficiency of the manual methods, the semi-automatic or automatic methods of building ontology are becoming the hotspot of current research. Concept is one of the most important parts composing the ontology, so the efficiency and precision of extracting concepts automatically from semi-structured web document directly determine the quality of ontology built automatically. The paper proposes a automatic ontology concept extraction model independent of the domain word library or core ontology, and the model can automatically extract the domain ontology concepts by mining the Chinese web documents quickly and efficiently.

关 键 词：本体学习 互信息 知识获取术 语抽取 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置]