摘要

The term 'Linked Data' describes online-retrievable formal descriptions of entities and their links to each other. Machines and humans alike can retrieve these descriptions and discover information about links to other entities. However, for human users it becomes difficult to browse descriptions of single entities because, in many cases, they are referenced in more than a thousand statements. In this demo paper we present SUMMARUM, a system that ranks triples and enables entity summaries for improved navigation within Linked Data. In its current implementation, the system focuses on DBpedia with the summaries being based on the PageRank scores of the involved entities.
机译:术语“链接数据”描述了实体及其相互链接的在线可获取形式描述。机器和人类都可以检索这些描述,并发现有关到其他实体的链接的信息。但是,对于人类用户而言,浏览单个实体的描述变得困难,因为在许多情况下,它们在上千个语句中被引用。在此演示文件中,我们介绍SUMMARUM,该系统对三元组进行排名,并启用实体摘要以改进链接数据内的导航。在当前的实现中,系统专注于DBpedia,其摘要基于所涉及实体的PageRank分数。

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号