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从链接的开放数据生成可能的统计解释

Generating Possible Interpretations for Statistics from Linked Open Data
课程网址: http://videolectures.net/eswc2012_paulheim_linked_data/  
主讲教师: Heiko Paulheim
开课单位: 曼海姆大学
开课时间: 2012-07-04
课程语种: 英语
中文简介:
统计数字在我们的日常生活中非常普遍。每天都有新的统计数据公布,显示不同城市的生活质量、不同国家的腐败指数等等。另一方面,解释这些统计数字是一项艰巨的任务。通常,统计数据只收集很少的属性,很难提出假设来解释,例如,为什么一个城市的感知生活质量高于另一个城市。在本文中,我们介绍了Explain-a-LOD,这是一种使用链接开放数据的数据来生成解释统计的假设的方法。我们展示了一个实现的原型,并通过分析用户研究中这些假设的感知质量来比较生成假设的不同方法。
课程简介: Statistics are very present in our daily lives. Every day, new statistics are published, showing the perceived quality of living in different cities, the corruption index of different countries, and so on. Interpreting those statistics, on the other hand, is a difficult task. Often, statistics collect only very few attributes, and it is difficult to come up with hypotheses that explain, e.g., why the perceived quality of living in once city is higher than in another. In this paper, we introduce Explain-a-LOD, an approach which uses data from Linked Open Data for generating hypotheses that explain statistics. We show an implemented prototype and compare different approaches for generating hypotheses by analyzing the perceived quality of those hypotheses in a user study.
关 键 词: 统计数据; 链接公开; 感知质量
课程来源: 视频讲座网
数据采集: 2020-12-07:yxd
最后编审: 2020-12-07:yxd
阅读次数: 34