Reasoning Web. Learning, Uncertainty, Streaming, and Scalability Reasoning Web. Learning, Uncertainty, Streaming, and Scalability

Reasoning Web. Learning, Uncertainty, Streaming, and Scalability

14th International Summer School 2018, Esch-sur-Alzette, Luxembourg, September 22–26, 2018, Tutorial Lectures

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출판사 설명

The research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently  received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shownuseful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains.

장르
컴퓨터 및 인터넷
출시일
2018년
9월 14일
언어
EN
영어
길이
248
페이지
출판사
Springer International Publishing
판매자
Springer Nature B.V.
크기
9.8
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