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Titlebook: Semantic Technology; 6th Joint Internatio Yuan-Fang Li,Wei Hu,Yang Liu Conference proceedings 2016 Springer International Publishing AG 201

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发表于 2025-3-21 18:57:23 | 显示全部楼层 |阅读模式
书目名称Semantic Technology
副标题6th Joint Internatio
编辑Yuan-Fang Li,Wei Hu,Yang Liu
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Semantic Technology; 6th Joint Internatio Yuan-Fang Li,Wei Hu,Yang Liu Conference proceedings 2016 Springer International Publishing AG 201
描述.This book constitutes the thoroughly refereed proceedings of the 6th Joint International Semantic Technology Conference, JIST 2016, held in Singapore, Singapore, in November 2016. The main topics of JIST 2016 include among others ontology and reasoning; linked data; knowledge graph. The JIST 2016 conference consists of two keynotes, a main technical track, including (full and short papers) from the research and the in-use tracks, a Poster and Demo session, a workshop and two tutorials...The 16 full and 8 short papers presented were carefully reviewed and selected from 34 submissions. The papers cover the following topics: ontology and data management; linked data; information retrieval and knowledge discovery; RDF and query; knowledge graph; application of semantic technologies..
出版日期Conference proceedings 2016
关键词data quality; database integration; meta-modeling; ontology; semantic Web; benchmarking; failure recovery;
版次1
doihttps://doi.org/10.1007/978-3-319-50112-3
isbn_softcover978-3-319-50111-6
isbn_ebook978-3-319-50112-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2016
The information of publication is updating

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0302-9743 and selected from 34 submissions. The papers cover the following topics: ontology and data management; linked data; information retrieval and knowledge discovery; RDF and query; knowledge graph; application of semantic technologies..978-3-319-50111-6978-3-319-50112-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
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How Can Reasoner Performance of ABox Intensive Ontologies Be Predicted? been the prediction of how much time a particular task for a given ontology will consume. Several approaches have adopted different machine learning techniques to predict time consumption of ontologies already. However, these studies focused on capturing general aspects of the ontologies (i.e., mai
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Inquiry into RDF and OWL Semanticsiscussion of Russell’s ., which was developed in order to solve . appeared at the last stage in the history of set theory. This paper briefly summarize some of set theories, and reviews the RDF and OWL Semantics with higher order classes from the view of Russell’s .. Then, a set of criteria is propo
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An Empirical Study on Property Clustering in Linked Dataally gathered to describe a person’s name. However, existing automated approaches to property clustering remain far from satisfactory for an open domain like Linked Data. In this paper, we firstly investigated the relatedness between properties using five different measures. Then, we employed three
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