Reasoning Web. Learning, Uncertainty, Streaming, and Scalability: 14th International Summer School 2018, Esch-sur-Alzette, Luxembourg, September ... Lectures (Lecture Notes in Computer Science)
暫譯: 推理網路：學習、不確定性、串流與可擴展性：第14屆國際暑期學校2018，盧森堡艾希爾阿爾澤特，九月... 講座（計算機科學講義）

This volume contains lecture notes of the 14th Reasoning Web Summer School (RW 2018), held in Esch-sur-Alzette, Luxembourg, in September 2018.

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 shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains.