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检测用于数据预取的SPARQL查询模板

Detecting SPARQL Query Templates for Data Prefetching
课程网址: http://videolectures.net/eswc2013_lorey_data/  
主讲教师: Johannes Lorey, Laura Hollink
开课单位: 波茨坦大学
开课时间: 2013-07-08
课程语种: 英语
中文简介:
公开可用的关联数据存储库提供大量信息。通过利用Sparql,网站和服务可以使用这些数据并以用户友好的形式呈现它,例如,在混搭中。为了收集此任务的RDF三元组,机器代理通常会针对Sparql端点发出具有重复模式的类似结构化查询。这些查询通常仅在少数单个三元模式部分中有所不同,例如资源标签或对象中的文字。我们提出了一种在查询中检测此类重复模式的方法,并介绍了查询模板的概念,这些模板表示展示这些重现的类似查询的集群。我们描述了一种匹配算法来提取查询模板,并说明利用这些模板预取数据的好处。最后,我们使用来自真实Sparql查询日志的结果评论我们的方法的适用性。
课程简介: Publicly available Linked Data repositories provide a multitude of information. By utilizing Sparql, Web sites and services can consume this data and present it in a user-friendly form, e.g., in mash-ups. To gather RDF triples for this task, machine agents typically issue similarly structured queries with recurring patterns against the Sparql endpoint. These queries usually differ only in a small number of individual triple pattern parts, such as resource labels or literals in objects. We present an approach to detect such recurring patterns in queries and introduce the notion of query templates, which represent clusters of similar queries exhibiting these recurrences. We describe a matching algorithm to extract query templates and illustrate the benefits of prefetching data by utilizing these templates. Finally, we comment on the applicability of our approach using results from real-world Sparql query logs.
关 键 词: 关联数据; 机器代理; 结构化查询
课程来源: 视频讲座网
最后编审: 2019-04-14:lxf
阅读次数: 27