图 书 馆
大图形数据面板Big Graph Data Panel |
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| 课程网址: | http://videolectures.net/iswc2012_big_graph_data/ |
| 主讲教师: | Frank van Harmelen; Tim Berners-Lee; John Giannandrea; Mike Stonebreaker; Bryan Thompson |
| 开课单位: | 麻省理工学院 |
| 开课时间: | 2012-12-03 |
| 课程语种: | 英语 |
| 中文简介: |  语义Web是否需要任何中央基础结构？ （毕竟，这是一个Web？） 还是少数几个大型单一所有者基础结构将主导语义Web，就像它们现在主导当前Web？ 这样的基础架构是否将基于标准的关系模型？ 还是基于MapReduce中心键/值对？ Google的（集中式）知识图式是针对语义* Web *吗？ / p> 三元店供应商是否只是在重塑旧的数据库轮子？ 集群式MapReduce之类的解决方案的作用是什么，它们在处理语义Web数据方面的限制在哪里？ |
| 课程简介: | he Semantic Web / Linked Data has grown immensely over the past years. When the Semantic Web community started working over a decade ago the main question was where to get the data from. By now the question of how to process ever increasing amount of semantic/linked data has come to people's utmost attention. The goal of this panel is to shed light on the various approaches/options for Big Graph Data processing. Possible questions include: Does the Semantic Web need any central infrastructures? (It's a Web, after all?) Or will a handful of large single-owner infrastructures dominate the Semantic Web, just as they now dominate the current Web? And if so, will such infrastructures be based on the standard relational model? Or on MapReduce-centric key/value-pairs? Is Google's (centralised) Knowledge Graph anathema to the Semantic *Web* ? Are triplestore vendors just reinventing the old database wheels? What is the role of clustered MapReduce-like solutions and where are their limits for processing semantic web data? |
| 关 键 词: | 大图形数据; 语义Web; 数据链接 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-11-04：zyk |
| 最后编审: | 2020-11-04：zyk |
| 阅读次数: | 3 |