随着城市大脑建设进程的推进,城市中积累了大量的物联网(IoT)设备和数据,利用海量设备数据对问题进行分析和溯源,对于城市大脑建设具有重要意义。该文基于资源描述框架和智能物联网协议概念,提出一种以城市物联网本体为基础的城市大脑知识图谱建设方法,城市大脑知识图谱模型融合多源异构数据,覆盖城市基本要素,实现对城市要素的全面感知和深度认知。该文重点探究了城市事件本体中的事件抽取,设计了一种新颖的语言模型框架对事件类型和论元联合抽取,与单模型分析对比,该联合模型较单模型的事件类型和论元F1值分别提高0.4%和2.7%,在时间和模型复杂度上,较单模型级联也有更好效果。最后,该研究对知识图谱技术与人工智能、多传感器融合、GIS等新一代信息技术交叉融合方面进行了探究分析,为城市治理和服务应用场景提供理论依据。
Abstract
We propose a methodology for constructing a city brain knowledge graph (CBKG) based on the resource description framework, IoT protocol and digital twin. Knowledge ontology and sub-ontology models for city brain are designed by coupling city elements and smart IoT standards. This knowledge graph model can integrate multi-source heterogeneous data, and therefore serving in the brain knowledge system for city-level intelligent operating system. We explore the event extraction under the city event ontology and designe a novel joint model to extract the event meta-theory. The results suggest that CBKG can support the intelligent management of the city in decision-makings. Future application of CBKG will couple with artificial intelligence, multi-sensor technologies, geographic information systems, and etc.
关键词
城市大脑 /
知识图谱 /
物联网 /
本体构建 /
事件抽取
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Key words
city brain /
knowledge graph /
Internet of things /
ontology construction /
event extraction
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参考文献
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