基于结构相似性的语义网信息检索

Information retrieval based on structural similarity for semantic web

语义网是提高网络信息检索质量的重要途径。利用现在流行的Web信息检索系统,扩展其处理语义Web文档中的语义评注的能力,采用更有效的文档分类算法,将语义Web文档组织成蔟,提高检索质量。介绍的算法与标准的基于图匹配算法相比,计算代价降低,便于后续的存储、抽取和处理等工作。

The semantic web offers a promising solution to improve the quality of information retrieval on the world wide web. Prevalent web information retrieval systems are extended to handle annotations in semantic web languages. Moreover, an effective document categorization algorithm is used to semi-structured semantic web documents （SWDs） which significantly differs from standard methods based on graph-matching algorithms. SWDs is grouped into clusters so that different storage, retrieval, and processing techniques are effectively exploited.