物联网语义关联和决策方法的研究

冯建周; 宋沙沙; 孔令富

doi:10.16383/j.aas.2016.c150885

物联网语义关联和决策方法的研究

doi: 10.16383/j.aas.2016.c150885

冯建周^1,2, ,,
宋沙沙^1,2,,
孔令富^1,2,

1.
燕山大学信息科学与工程学院秦皇岛 066004
2.
河北省虚拟技术与系统集成重点实验室秦皇岛 066004

基金项目:

河北省自然科学基金 F2014203192

燕山大学博士基金 B845

详细信息

作者简介:
宋沙沙燕山大学信息科学与工程学院硕士研究生.2015年获得沈阳化工大学计算机科学与技术学院学士学位.主要研究方向为语义Web.E-mail:song@stumail.ysu.edu.cn

孔令富燕山大学信息科学与工程学院教授.1995年获得哈尔滨工业大学机械电子工程专业博士学位.主要研究方向为智能信息处理, 物联网工程.E-mail:lfkong@ysu.edu.cn

通讯作者:
冯建周燕山大学信息科学与工程学院副教授.2013年获燕山大学计算机应用技术专业博士学位.主要研究方向为语义Web, 服务计算. E-mail:fjzwxh@ysu.edu.cn

计量
- 文章访问数: 1993
- HTML全文浏览量: 409
- PDF下载量: 1264
- 被引次数: 9
出版历程
- 收稿日期: 2015-12-29
- 录用日期: 2016-05-16
- 刊出日期: 2016-11-01

Research on Semantic Association and Decision Method of the Internet of Things

FENG Jian-Zhou^{1,2
, ,},
SONG Sha-Sha^{1,2
,},
KONG Ling-Fu^{1,2
,}

1.
School of Information Science and Engineering, Yanshan University, Qinhuangdao 066004
2.
Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Qinhuangdao 066004

Funds:

Supported by Natural Science Foundation of Hebei Province F2014203192

Doctoral Fund of Yanshan University B845

More Information

Author Bio:
Master student at the School of Information Science and Engineering, Yansh-an University. She received her bachelor degree from the School of Computer Science and Technology, Shenyang University of Chemical Technology in 2015. Her main re-search interest is semantic web.)E-mail:

Professor at the School of Information Science and En-gineering, Yanshan University. He re-ceived his Ph. D. degree in machinery and electronics en-gineering at Harbin Institute of Technology in 1995. His research interest covers intelligent information processing and the Internet of Things engineering.E-mail:

Corresponding author: FENG Jian-Zhou Associate pro-fessor at the School of Information Sci-ence and Engineering, Yanshan Univer-sity. He received his Ph. D. degree from computer appli-cation technology at Yanshan University in 2013. His re-search interest covers semantic web and service computing. Corresponding author of this paper.E-mail:fjzwxh@ysu.edu.cn

摘要

摘要: 物联网系统包含大量的感知设备，产生大量孤立和异构的感知数据，形成数据孤岛.如何将不同感知设备产生的数据进行有效的语义关联、构建跨域的数据关联模型、屏蔽数据异构性、实现综合智能决策是物联网研究的关键问题.本文以物联网系统为研究对象，从语义入手，构建以环境—资源—行为为核心的物联网本体模型；基于关联数据方法构建以行为关联模型和资源关联模型为核心的物联网语义关联网络；提出一种基于事件的推理算法实现语义推理，从而更好地实现对物联网系统的智能决策；最后，通过两个智能家居系统的实例验证了本文方法的可行性，通过构建不同方法的查询实例验证了本文方法的优越性.
- 物联网 /
- 数据孤岛 /
- 领域本体 /
- 语义关联 /
- 数据推理
Abstract: The Internet of Things (IoT) system contains a large number of sensing devices, as a result, massive isolated and heterogeneous data are generated and forming isolated islands of data. It is a key issue how to realize the effective semantic association of data produced by different sensing devices, and to construct a cross-domain data correlation model, so as to solve data heterogeneity and realize intelligent decision making. In this paper, with the IoT system as the research object, an IoT ontology model is built with environment-resource-behavior as the core. Based on linked data method, the IoT semantic linked network is constructed with the behavior linked model and the resource linked model as the core. And a reasoning algorithm based on event has been put forward to realize the semantic reasoning, so as to better realize the intelligent decision-making of the IoT system. At last, its feasibility is verified through two examples of smart home system, and its superiority is verified through building different query instances.
- The Internet of Things (IoT) /
- data island /
- domain ontology /
- semantic association /
- data reasoning

HTML全文

图 1 物联网领域本体的层次结构

Fig. 1 The hierarchical structure of IoT domain ontology

下载: 全尺寸图片幻灯片

图 2 E-R-B模型

Fig. 2 E-R-B model

下载: 全尺寸图片幻灯片

图 3 行为关联模型

Fig. 3 Behavior association model

下载: 全尺寸图片幻灯片

图 4 资源关联模型

Fig. 4 Resources association model

下载: 全尺寸图片幻灯片

图 5 部分智能家居本体图

Fig. 5 Part of the smart home ontology figure

下载: 全尺寸图片幻灯片

图 6 智能家居数据关联模型

Fig. 6 Data association model of smart home

下载: 全尺寸图片幻灯片

图 7 Jena推理结果

Fig. 7 Jena reasoning result

下载: 全尺寸图片幻灯片

表 1 不同方法的查得率和正确率比较表

Table 1 The comparison table of detection\rate and accuracy

方法编号语义标注和数据关联事件推理查得率(%) 正确率(%)

1 无无 36 24

2 有无 72 60

3 有有 98 98

下载: 导出CSV

参考文献(18)

[1]	Berners-Lee T, Hendler J, Lassila O. The semantic web. Scientific American, 2001, 284(5): 34-43 doi: 10.1038/scientificamerican0501-34
[2]	Nebot V, Berlanga R. Finding association rules in semantic web data. Knowledge-Based Systems, 2012, 25(1): 51-62 doi: 10.1016/j.knosys.2011.05.009
[3]	Sheth A, Henson C, Sahoo S S. Semantic sensor web. IEEE Internet Computing, 2008, 12(4): 78-83 doi: 10.1109/MIC.2008.87
[4]	Coccoli M, Torre I. Interacting with annotated objects in a Semantic Web of Things application. Journal of Visual Languages and Computing, 2014, 25(6): 1012-1020 doi: 10.1016/j.jvlc.2014.09.008
[5]	De S, Barnaghi P, Bauer M, Meissner S. Service modelling for the Internet of Things. In: Proceedings of the 2011 Federated Conference on Computer Science and Information Systems (FedCSIS). Szczecin, Poland: IEEE, 2011. 949-955 http://www.baidu.com/link?url=OvojrU2e-W230Kx7b6OiOZHF1nAQ43eCBQVzj269-RdI5YQu7OZKXbybExF6dq9CxZMJBWx05qVxMnyBcLzEzr1HUHLgK5f4IiHCTLBJEm_FRgMu53thtU1HwbeakhnmBe4s5pqpxJ-7eED1CVTHOJHuRZjUKWO4z-nnrf_DDn1lr4atbLnw2NtNViNjLPz4xMjxaNgdUILGFzeTnKHmIAuX52HWiwi0c0BjekdmkoPYPRWzwIEjDecrxJu5lEC04IBzXFs4-Nz7LpbMMcwBfNiCsJtas9KHJ4s0aYNsOa10cyvbEPQVwm7XG1_aPaAf&wd=&eqid=83cb549d00038a6900000005583948a7
[6]	Grau B C, Horrocks I, Motik B, Parsia B, Patel-Schneider P, Sattler U. OWL 2: the next step for OWL. Web Semantics: Science, Services, and Agents on the World Wide Web, 2008, 6(4): 309-322 doi: 10.1016/j.websem.2008.05.001
[7]	OWL-S: semantic markup for web services [Online], available: http://www.w3.org/Submission/OWL-S, November 22, 2004
[8]	Compton M, Barnaghi P, Bermudez L, García-Castro R, Corcho O, Cox S, Graybeal J, Hauswirth M, Henson C, Herzog A, Huang V, Janowicz K, Kelsey W D, Le Phuoc D, Lefort L, Leggieri M, Neuhaus H, Nikolov A, Page K, Passant A, Sheth A, Taylor K. The SSN ontology of the W3C semantic sensor network incubator group. Web Semantics: Science, Services, and Agents on the World Wide Web, 2012, 17: 25-32 doi: 10.1016/j.websem.2012.05.003
[9]	李戈, 魏强, 李力行, 金芝, 许焱, 郑丽伟. 物联网服务建模: 一种基于环境建模的方法. 中国科学: 信息科学, 2013, 43(10): 1198- 1218 http://www.cnki.com.cn/Article/CJFDTOTAL-PZKX201310002.htm Li Ge, Wei Qiang, Li Li-Xing, Jin Zhi, Xu Yan, Zheng Li-Wei. Environment based modeling approach for services in the Internet of Things. Science China: Information Science, 2013, 43(10): 1198-1218 http://www.cnki.com.cn/Article/CJFDTOTAL-PZKX201310002.htm
[10]	徐杨, 王晓峰, 何清漪. 物联网环境下多智能体决策信息支持技术. 软件学报, 2014, 25(10): 2325-2345 Xu Yang, Wang Xiao-Feng, He Qing-Yi. Internet of Things based information support system for multi-agent decision. Journal of Software, 2014, 25(10): 2325-2345
[11]	乔秀全, 章洋, 吴步丹, 程渤, 赵帅, 马华东, 陈俊亮. 事件驱动、面向服务的物联网服务提供方法. 中国科学: 信息科学, 2013, 43(10): 1219-1243 http://www.cnki.com.cn/Article/CJFDTOTAL-PZKX201310003.htm Qiao Xiu-Quan, Zhang Yang, Wu Bu-Dan, Cheng Bo, Zhao Shuai, Ma Hua-Dong, Chen Jun-Liang. An EDSOA-based services provisioning approach for Internet of Things. Science China: Information Science, 2013, 43(10): 1219-1243 http://www.cnki.com.cn/Article/CJFDTOTAL-PZKX201310003.htm
[12]	Cuzzola J, Jovanović J, Bagheria E, Gašević D. Evolutionary fine-tuning of automated semantic annotation systems. Expert Systems with Applications, 2015, 42(20): 6864- 6877 doi: 10.1016/j.eswa.2015.04.054
[13]	Tosi D, Morasca S. Supporting the semi-automatic semantic annotation of web services: a systematic literature review. Information and Software Technology, 2015, 61: 16-32 doi: 10.1016/j.infsof.2015.01.007
[14]	The D2R Project [Online], available: http://d2rq.org/, March 12,2012
[15]	张静, 马春娥. 如何利用D2R发布Linked data [Online], available: http://www.ibm.com/developerworks/cn/web/1003_ zhangjing_d2r/index.html, 2010年4月25日 Zhang Jing, Ma Chun-E. How to use D2R to publish linked data [Online], available:http://www.ibm.com/deve-loperworks/cn/web/1003_zhangjing_d2r/index.html, April 25, 2010
[16]	The Linked Data Project [Online], available: http://linked data.org/, April 16, 2015
[17]	The Jena Project [Online], available: http://jena.apache.org/, March 23, 2015
[18]	顾小东, 高阳. Rete算法: 研究现状与挑战. 计算机科学, 2012, 39(11): 8-12, 33 http://www.cnki.com.cn/Article/CJFDTOTAL-JSJA201211002.htm Gu Xiao-Dong, Gao Yang. Rete algorithm: current issues and future challenge. Computer Science, 2012, 39(11): 8- 12, 33 http://www.cnki.com.cn/Article/CJFDTOTAL-JSJA201211002.htm

施引文献

期刊类型引用(5)

1.	许思遥，曾健骏，张维彦，叶琪，朱焱. 基于大小语言模型协同增强的中文电子病历依存句法分析. 计算机科学. 2025(02): 253-260 . 百度学术
2.	沈春山，肖宗涛，徐德强. 一种面向自然语言交互接口语义分析的MNet方法研究. 小型微型计算机系统. 2023(02): 340-348 . 百度学术
3.	郭勇，赵康，潘力. 结合改进Bi-LSTM和CNN的文本情感分析. 信息技术. 2021(02): 50-55 . 百度学术
4.	林玉萍，郑尧月，郑好洁，张栋，王丛，李小棉，李颖玉，田智强. 基于医学影像分割方法的多模态语料库构建. 模式识别与人工智能. 2021(04): 353-360 . 百度学术
5.	张吉亮，尹兰. 基于Hadoop的文本分析平台实践. 安顺学院学报. 2020(01): 132-136 . 百度学术