Lee Chang-Shing, Jian Zhi-Wei, Huang Lin-Kai
Department of Information Management, Chang Jung Christian University, Tainan, Taiwan.
IEEE Trans Syst Man Cybern B Cybern. 2005 Oct;35(5):859-80. doi: 10.1109/tsmcb.2005.845032.
In this paper, a fuzzy ontology and its application to news summarization are presented. The fuzzy ontology with fuzzy concepts is an extension of the domain ontology with crisp concepts. It is more suitable to describe the domain knowledge than domain ontology for solving the uncertainty reasoning problems. First, the domain ontology with various events of news is predefined by domain experts. The document preprocessing mechanism will generate the meaningful terms based on the news corpus and the Chinese news dictionary defined by the domain expert. Then, the meaningful terms will be classified according to the events of the news by the term classifier. The fuzzy inference mechanism will generate the membership degrees for each fuzzy concept of the fuzzy ontology. Every fuzzy concept has a set of membership degrees associated with various events of the domain ontology. In addition, a news agent based on the fuzzy ontology is also developed for news summarization. The news agent contains five modules, including a retrieval agent, a document preprocessing mechanism, a sentence path extractor, a sentence generator, and a sentence filter to perform news summarization. Furthermore, we construct an experimental website to test the proposed approach. The experimental results show that the news agent based on the fuzzy ontology can effectively operate for news summarization.
本文提出了一种模糊本体及其在新闻摘要中的应用。具有模糊概念的模糊本体是具有清晰概念的领域本体的扩展。在解决不确定性推理问题方面，它比领域本体更适合描述领域知识。首先，领域专家预先定义包含各种新闻事件的领域本体。文档预处理机制将基于新闻语料库和领域专家定义的中文新闻词典生成有意义的术语。然后，术语分类器将根据新闻事件对有意义的术语进行分类。模糊推理机制将为模糊本体的每个模糊概念生成隶属度。每个模糊概念都有一组与领域本体的各种事件相关联的隶属度。此外，还开发了一个基于模糊本体的新闻智能体用于新闻摘要。该新闻智能体包含五个模块，包括检索智能体、文档预处理机制、句子路径提取器、句子生成器和句子过滤器，以执行新闻摘要。此外，我们构建了一个实验网站来测试所提出的方法。实验结果表明，基于模糊本体的新闻智能体能够有效地进行新闻摘要。
