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观察关联数据动态

Observing Linked Data Dynamics
课程网址: http://videolectures.net/eswc2013_kaefer_data/  
主讲教师: Olaf Hartig, Tobias Käfer
开课单位: 卡尔斯鲁厄理工学院
开课时间: 2013-07-08
课程语种: 英语
中文简介:
在本文中,我们介绍了动态关联数据观测台的设计和初步结果:一项长期实验,每周监测一组核心的八千种不同关联数据文档的两跳邻域。我们提供了用于对URI进行采样以监控,检索文档以及进一步爬行两跳邻域的一部分的方法。现在已经运行了六个月的实验,我们分析了迄今为止收集的数据所监控文档的动态。我们看一下核心文件的估计寿命,它们在线或离线的频率,它们改变的频率;我们进一步调查域级别趋势。接下来,我们将查看每周快照中核心文档的RDF内容中的更改,检查最常添加或删除的元素(即三元组,主题,谓词,对象,类)。此后,我们将了解可解除引用文档之间的链接如何随着时间的推移在两个跃点邻域中演变。
课程简介: In this paper, we present the design and first results of the Dynamic Linked Data Observatory: a long-term experiment to monitor the two-hop neighbourhood of a core set of eighty thousand diverse Linked Data documents on a weekly basis. We present the methodology used for sampling the URIs to monitor, retrieving the documents, and further crawling part of the two-hop neighbourhood. Having now run this experiment for six months, we analyse the dynamics of the monitored documents over the data collected thus far. We look at the estimated lifespan of the core documents, how often they go on-line or off-line, how often they change; we further investigate domain-level trends. Next we look at changes within the RDF content of the core documents across the weekly snapshots, examining the elements (i.e., triples, subjects, predicates, objects, classes) that are most frequently added or removed. Thereafter, we look at how the links between dereferenceable documents evolves over time in the two-hop neighbourhood.
关 键 词: 关联数据; 两跳邻域; 域级别趋势
课程来源: 视频讲座网
最后编审: 2019-04-14:lxf
阅读次数: 15