图 书 馆
代表性Representativeness |
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| 课程网址: | http://videolectures.net/iswc2018_soulet_representativeness_knowl... |
| 主讲教师: | Arnaud Soulet |
| 开课单位: | 弗朗索瓦·拉伯莱大学 |
| 开课时间: | 2018-11-22 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Knowledge bases (KBs) such as DBpedia, Wikidata, and YAGO contain a huge number of entities and facts. Several recent works induce rules or calculate statistics on these KBs. Most of these methods are based on the assumption that the data is a representative sample of the studied universe. Unfortunately, KBs are biased because they are built from crowdsourcing and opportunistic agglomeration of available databases. This paper aims at approximating the representativeness of a relation within a knowledge base. For this, we use the Generalized Benford's law, which indicates the distribution expected by the facts of a relation. We then compute the minimum number of facts that have to be added in order to make the KB representative of the real world. Experiments show that our unsupervised method applies to a large number of relations. For numerical relations where ground truths exist, the estimated representativeness proves to be a reliable indicator. |
| 关 键 词: | 众包和可用数据库; 近似知识库; 知识库的规则 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-01-14：cyh |
| 最后编审: | 2023-01-16：cyh |
| 阅读次数: | 26 |