摘要
随着信息的快速更新,知识本体经常不能满足用户的需求,提出了一个能把新关键词插入到相应本体中的领域本体更新方法。该方法用LSA(潜在语义分析)来获取关键词的语义特征,然后把LSA矩阵转换成基于Web文档的高维空间。通过比较高维空间中关键词和相应本体概念来获取关键词和概念之间的相似值,如果这个值低于某个设定值,这个关键词就插入到领域本体概念节点中。初步的试验结果表明了这个方法的有效性。
The information is changed fast on the Intenet, so the knowledge on the ontology often can not really meet the user＇ s requirement. Therefore, an ontology renewable method is proposed, which can insert new keywords into a corresponding constructed ontology. The novel method uses LSA, latent semantic analysis, to strengthen the semantic characteristic ofkeywords and transforms the LSA matrix to a high dimensional space based on collected web pages. The similar values between keywords and concepts are gotten by comparing the high dimension keyword to the corresponding constructed ontology concepts. If a keyword has highest similarity value between it and one of concepts on the domain and similarity value less than a threshold, the keyword will be inserted into the offspring of the concept on the domain ontology. The primary experiment results indicated the method is useful.
出处
《计算机工程与设计》
CSCD
北大核心
2011年第8期2833-2835,2869,共4页
Computer Engineering and Design
基金
国家自然科学基金项目(60873104)
关键词
语义WEB
本体
奇异值分解
LSA矩阵
相似度
semantic web
ontology
singular value decomposition
LSA matrix
similarity
