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排序语义Web查询的近似答案

Ranking Approximate Answers to Semantic Web Queries
课程网址: http://videolectures.net/eswc09_poulovassilis_raats/  
主讲教师: Alexandra Poulovassilis
开课单位: 伦敦大学学院
开课时间: 2009-07-28
课程语种: 英语
中文简介:
我们考虑用户在不知道其结构的情况下查询诸如RDF之类的半结构化数据的问题。在这些情况下,如果查询系统可以执行用户的查询与数据的近似匹配并且可以根据它们与原始查询的匹配程度对答案进行排名,则是有帮助的。我们展示了我们的近似匹配框架允许我们结合RDFS推理规则以及近似的标准概念,例如编辑距离,从而捕获语义和句法近似。我们采用的查询语言包含常规路径查询的连接,因此包括为SPARQL提出的扩展,允许使用正则表达式查询路径。我们提供了一种增量查询评估算法,该算法在多项式时间内运行,并按排名顺序向用户返回答案。
课程简介: We consider the problem of a user querying semistructured data such as RDF without knowing its structure. In these circumstances, it is helpful if the querying system can perform an approximate matching of the user's query to the data and can rank the answers in terms of how closely they match the original query. We show that our approximate matching framework allows us to incorporate RDFS inference rules as well as standard notions of approximation such as edit distance, thereby capturing semantic as well as syntactic approximations. The query language we adopt comprises conjunctions of regular path queries, thus including extensions proposed for SPARQL to allow for querying paths using regular expressions. We provide an incremental query evaluation algorithm which runs in polynomial time and returns answers to the user in ranked order.
关 键 词: 半结构化数据; 查询系统; 近似匹配框架
课程来源: 视频讲座网
最后编审: 2020-10-22:chenxin
阅读次数: 39