基于关键词的语义网数据查询研究综述  

Keyword-based Search on Semantic Web Data:The State of the Art

作　　者：李慧颖[1] 瞿裕忠[2] 

机构地区：[1]东南大学计算机科学与工程学院,南京210096 [2]南京大学计算机科学与技术系,南京210093

出　　处：《计算机科学》2011年第7期18-23,50,共7页Computer Science

基　　金：国家自然科学基金(60973024);江苏省自然科学基金(BK2008290)资助

摘　　要：语义网数据的关键词查询是语义网研究的一个重要问题。首先给出语义网数据关键词查询的相关定义。根据研究目标不同,将已有解决方案分为混合型和非混合型的语义网数据关键词查询,后者又分为K-A和K-Q-A两种查询方法。调研了上述分类中当前常用的解决方案和研究进展。在此基础上,进一步介绍并比较了8个具有代表性的语义网数据关键词查询工作。最后讨论存在的挑战,并指出未来可能的研究方向。The growth of the Semantic Web has seen a rapid increase in the amount of RDF data.Meanwhile,the demand for access to RDF data without detailed knowledge of RDF query languages is increasing.In this paper,some definitions in terms of keywords-based search on Semantic Web data were firstly presented.Then,a large number of popular existing solutions were surveyed according to hybrid and non-hybrid style（including K-A means and K-Q-A means）.In addition,eight representative systems were introduced and compared with each other based on different facets,and their unique features were highlighted in details.Finally,some remaining challenges were discussed,and some future research directions were pointed out.

关 键 词：关键词查询 RDF数据 TOP-K 语义网 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]