传感器数据的语义探索

Web-KR '14 Pub Date : 2014-11-03 DOI:10.1145/2663792.2663800
Snehasish Banerjee, Abhishek Mishra, R. Dasgupta
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引用次数: 5

摘要

随着政府和管理部门发布开放的关联数据,以及全球传感器部署的逐步兴起,对传感器和关联数据的组合进行语义查询已成为提供多种智能城市服务和应用的需求。数据以三元组(RDF)的形式表示,概念和关系以本体论(OWL)的形式表示,相应的查询语言是根据语义Web标准的SPARQL。本文提出了一种传感器探索系统,该系统以一组关键词、上下文、数据、学习和背景知识作为输入,并产生预期的结果作为输出。该系统试图保持底层语义web技术对最终用户透明。讨论了相关挑战和未来工作的范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semantic Exploration of Sensor Data
With governments and administrations releasing open linked data, and with the gradual rise of sensor deployments across the world, semantic queries on the combined sensor and linked data has become a need to provide several intelligent smart city services and applications. The data is represented in form of triples (RDF), concepts and relations in form of ontologies (OWL) and the corresponding query language is SPARQL as per standards of Semantic Web. In this paper, a system for sensor exploration is presented, which takes a set of keywords, context, data, learned and background knowledge as input and produces the intentioned result as output. The system tries to keep the underlying semantic web technologies transparent to the end user. The relevant challenges and the scope of future work is also discussed.
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