多源道路智能选取的本体知识推理方法

doi:10.11947/j.AGCS.2022.20210168

摘要/Abstract

摘要： 大数据时代道路数据来源日益增多，跨数据源的道路选取面临巨大挑战。本文针对数据语义不一致问题，提出一种基于本体知识推理的多源道路选取方法。首先，将1：5万基本比例尺地形图道路数据作为基础案例，将四维图新导航电子地图和开放街道地图中的道路数据作为试验数据，基于stroke计算道路等级、长度、连通度、接近度、中介度特征项，提取特征项概念并构建本体；然后，从语义特征项和数值特征项两方面计算本体概念相似性，建立基础案例与试验数据间的关联关系；最后，基于本体和语义网规则语言定义本体通用、语义特征、数值特征三类选取规则，实现跨数据源道路选取的过程性知识推理。试验表明，本文方法可基于本体概念相似性度量消除语义差异，同时利用语义网规则语言进行知识推理，可实现多源道路数据向基本比例尺数据的智能选取。

关键词: 道路选取, 多源数据, 本体, 相似性, 语义网规则语言

Abstract: In the era of big data, multi-source data is increasing. However, there is a semantic inconsistency among multi-source data, we propose an intelligent road selection method based on ontology knowledge reasoning. In this paper, we use basic scale map as basic case and use navigation data and OSM data as experimental data. Features such as grade, length, degree, closeness and betweenness are calculated based on road stroke, and their concepts are extracted to construct a road selection ontology. In order to correlate basic case with experimental data, conceptual similarity is calculated from semantic feature and numerical feature. Then, ontology and semantic web rule language are used to define road selection rules and reason the process knowledge of cartographic generalization, which realize the automatic selection of multi-source road data. The experiments indicate that our method can effectively eliminate the semantic inconsistency among multi-source data to realize the road intelligent selection in similar areas.

Key words: road selection, multi-source data, ontology, similarity, semantic web rule language

中图分类号:

P208

郭漩, 钱海忠, 王骁, 刘俊楠, 任琰, 赵钰哲, 陈国庆. 多源道路智能选取的本体知识推理方法[J]. 测绘学报, 2022, 51(2): 279-289.

GUO Xuan, QIAN Haizhong, WANG Xiao, LIU Junnan, REN Yan, ZHAO Yuzhe, CHEN Guoqing. Ontology knowledge reasoning method for multi-source intelligent road selection[J]. Acta Geodaetica et Cartographica Sinica, 2022, 51(2): 279-289.

参考文献

[1] 武芳, 巩现勇, 杜佳威. 地图制图综合回顾与前望[J]. 测绘学报, 2017, 46(10):1645-1664. DOI:10.11947/j.AGCS.2017.20170287. WU Fang, GONG Xianyong, DU Jiawei. Overview of the research progress in automated map generalization[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10):1645-1664. DOI:10.11947/j.AGCS.2017.20170287.
[2] 何宗宜, 宋鹰. 普通地图编制[M]. 武汉:武汉大学出版社, 2015. HE Zongyi, SONG Ying. General map compilation[M]. Wuhan:Wuhan University Press, 2015.
[3] 王家耀, 李志林, 武芳. 数字地图综合进展[M]. 北京:科学出版社, 2011. WANG Jiayao, LI Zhilin, WU Fang. Advances in digital map generalization[M]. Beijing:Science Press, 2011.
[4] 曹炜威, 张红, 何晶, 等. 顾及结构和几何特征的道路自动选取方法[J]. 武汉大学学报(信息科学版), 2017, 42(4):520-524. CAO Weiwei, ZHANG Hong, HE Jing, et al. Road selection considering structural and geometric properties[J]. Geomatics and Information Science of Wuhan University, 2017, 42(4):520-524.
[5] 祝国瑞, 郭礼珍, 尹贡白, 等. 地图设计与编绘[M]. 武汉:武汉大学出版社, 2001. ZHU Guorui, GUO Lizhen, YIN Gongbai, et al. Map design and compilation[M]. Wuhan:Wuhan University Press, 2001.
[6] 胡云岗, 陈军, 李志林, 等. 基于网眼密度的道路选取方法[J]. 测绘学报, 2007, 36(3):351-357. HU Yungang, CHEN Jun, LI Zhilin, et al. Selective omission of road features based on mesh density for digital map generalization[J]. Acta Geodaetica et Cartographica Sinica, 2007, 36(3):351-357.
[7] THOMSON R C, RICHARDSON D E. The ‘good continuation’ principle of perceptual organization applied to the generalization of road networks[C]//Proceedings of 19th International Cartographic Conference. Ottawa:ICA, 1999:1215-1223.
[8] 陈波, 武芳, 钱海忠. 道路网自动选取方法研究[J]. 中国图象图形学报, 2008, 13(12):2388-2393. CHEN Bo, WU Fang, QIAN Haizhong. Study on road networks' auto-selection algorithms[J]. Journal of Image and Graphics, 2008, 13(12):2388-2393.
[9] 徐柱, 刘彩凤, 张红, 等. 基于路划网络功能评价的道路选取方法[J]. 测绘学报, 2012, 41(5):769-776. XU Zhu, LIU Caifeng, ZHANG Hong, et al. Road selection based on evaluation of stroke network functionality[J]. Acta Geodaetica et Cartographica Sinica, 2012, 41(5):769-776.
[10] 杨敏, 艾廷华, 周启. 顾及道路目标stroke特征保持的路网自动综合方法[J]. 测绘学报, 2013, 42(4):581-587, 594. YANG Min, AI Tinghua, ZHOU Qi. A method of road network generalization considering stroke properties of road object[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(4):581-587, 594.
[11] 何海威, 钱海忠, 刘海龙, 等. 道路网层次骨架控制的道路选取方法[J]. 测绘学报, 2015, 44(4):453-461, 470. DOI:10.11947/j.AGCS.2015.20130787. HE Haiwei, QIAN Haizhong, LIU Hailong, et al. Road network selection based on road hierarchical structure control[J]. Acta Geodaetica et Cartographica Sinica, 2015, 44(4):453-461, 470. DOI:10.11947/j.AGCS.2015.20130787.
[12] 邓红艳, 武芳, 翟仁健, 等. 基于遗传算法的道路网综合模型[J]. 武汉大学学报(信息科学版), 2006, 31(2):164-167. DENG Hongyan, WU Fang, ZHAI Renjian, et al. A generalization model of road networks based on genetic algorithm[J]. Geomatics and Information Science of Wuhan University, 2006, 31(2):164-167.
[13] 郭敏, 钱海忠, 黄智深, 等. ID3决策树推理模型及其在道路网选取中的应用[J]. 测绘科学技术学报, 2012, 29(4):308-312. GUO Min, QIAN Haizhong, HUANG Zhishen, et al. ID3 decision tree oriented knowledge reasoning model and its application in road network selection[J]. Journal of Geomatics Science and Technology, 2012, 29(4):308-312.
[14] 李进. 基于BP神经网络的道路网选取方法研究[D]. 南京:南京大学, 2014. LI Jin. Study on the road network selection methods based on the BP neural network[D]. Nanjing:Nanjing University, 2014.
[15] 郭敏, 钱海忠, 黄智深, 等. 道路网智能选取的案例类比推理法[J]. 测绘学报, 2014, 43(7):761-770. DOI:10.13485/j.cnki.11-2089.2014.0120. GUO Min, QIAN Haizhong, HUANG Zhishen, et al. Intelligent road-network selection using cases based reasoning[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(7):761-770. DOI:10.13485/j.cnki.11-2089.2014.0120.
[16] 曾兴国. 本体驱动下的网络专题地图制图服务模型研究[D]. 武汉:武汉大学, 2013. ZENG Xingguo. Research on ontology driven web thematic mapping service model[D]. Wuhan:Wuhan University, 2013.
[17] 赵云鹏, 孙群, 刘新贵, 等. 面向地理实体的语义相似性度量方法及其在道路匹配中的应用[J]. 武汉大学学报(信息科学版), 2020, 45(5):728-735. ZHAO Yunpeng, SUN Qun, LIU Xingui, et al. Geographical entity-oriented semantic similarity measurement method and its application in road matching[J]. Geomatics and Information Science of Wuhan University, 2020, 45(5):728-735.
[18] 谭永滨, 李霖, 王伟, 等. 本体属性的基础地理信息概念语义相似性计算模型[J]. 测绘学报, 2013, 42(5):782-789. TAN Yongbin, LI Lin, WANG Wei, et al. Semantic similarity measurement model between fundamental geographic information concepts based on ontological property[J]. Acta Geodaetica et Cartographica Sinica, 2013, 42(5):782-789.
[19] LIU Junnan, LIU Haiyan, CHEN Xiaohui, et al. A heterogeneous geospatial data retrieval method using knowledge graph[J]. Sustainability, 2021, 13(4):113042005.
[20] CHEN Shaoli, YI Jianjun, JIANG Hui, et al. Ontology and CBR based automated decision-making method for the disassembly of mechanical products[J]. Advanced Engineering Informatics, 2016, 30(3):564-584.
[21] 辜丽川. 基于CBR-Ontology的农作物病虫害防控智能决策支持系统研究[D]. 合肥:合肥工业大学, 2015. GU Lichuan. Study on crop pest control intelligent decision-making system based on CBR-Ontology[D]. Hefei:Hefei University of Technology, 2015.
[22] 邓敏, 陈雪莹, 唐建波, 等. 一种顾及道路交通流量语义信息的路网选取方法[J]. 武汉大学学报(信息科学版), 2020, 45(9):1438-1447. DENG Min, CHEN Yueying, TANG Jianbo, et al. A method for road network selection considering the traffic flow semantic information[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9):1438-1447.
[23] ZHOU Qi, LI Zhilin. A comparative study of various strategies to concatenate road segments into strokes for map generalization[J]. International Journal of Geographical Information Science, 2012, 26(4):691-715.
[24] CHEN Jun, HU Yungang, LI Zhilin, et al. Selective omission of road features based on mesh density for automatic map generalization[J]. International Journal of Geographical Information Science, 2009, 23(8):1013-1032.
[25] LIU Xingjian, ZHAN F B, AI Tinghua. Road selection based on Voronoi diagrams and "strokes" in map generalization[J]. International Journal of Applied Earth Observation and Geoinformation, 2010, 12 Suppl 2:S194-S202.
[26] 田晶, 罗云, 林镠鹏, 等. 两种道路选取策略的比较研究[J]. 武汉大学学报(信息科学版), 2019, 44(2):310-316. TIAN Jing, LUO Yun, LIN Liupeng, et al. A comparative study of two strategies of road network selection[J]. Geomatics and Information Science of Wuhan University, 2019, 44(2):310-316.
[27] 刘纪平, 栗斌, 石丽红, 等. 一种本体驱动的地理空间事件相关信息自动检索方法[J]. 测绘学报, 2011, 40(4):502-508. LIU Jiping, LI Bin, SHI Lihong, et al. An automated retrieval method of geo-spatial event information based on ontology[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(4):502-508.
[28] 张军伟, 王念滨, 黄少滨, 等. 二分K均值聚类算法优化及并行化研究[J]. 计算机工程, 2011, 37(17):23-25. ZHANG Junwei, WANG Nianbin, HUANG Shaobin, et al. Research on bisecting K-means clustering algorithm optimization and parallelism[J]. Computer Engineering, 2011, 37(17):23-25.
[29] LI Wenwen, RASKIN R, GOODCHILD M F. Semantic similarity measurement based on knowledge mining:an artificial neural net approach[J]. International Journal of Geographical Information Science, 2012, 26(8):1415-1435.
[30] LIU Hongzhe, BAO Hong, XU De. Concept vector for similarity measurement based on hierarchical domain structure[J]. Computing and Informatics, 2011, 30(5):881-900.
[31] QUINTERO R, TORRES-RUIZ M, MENCHACA-MENDEZ R, et al. DIS-C:conceptual distance in ontologies, a graph-based approach[J]. Knowledge and Information Systems, 2019, 59(1):33-65.
[32] 周志华. 机器学习[M]. 北京:清华大学出版社, 2016. ZHOU Zhihua. Machine learning[M]. Beijing:Tsinghua University Press, 2016.
[33] 陈德彦, 赵宏, 张霞. 专家视图与本体视图的语义映射方法[J]. 软件学报, 2020, 31(9):2855-2882. CHEN Deyan, ZHAO Hong, ZHANG Xia. Semantic mapping methods between expert view and ontology view[J]. Journal of Software, 2020, 31(9):2855-2882.
[34] 徐享忠, 汤再江, 杨建东, 等. 本体理论与工程应用[M]. 北京:国防工业出版社, 2019. XU Xiangzhong, TANG Zaijiang, YANG Jiandong, et al. Theory and engineering application of ontology[M]. Beijing:National Defense Industry Press, 2019.
[35] 辛跃. 基于本体知识库的贵州电网应急调度指挥平台决策支持系统研究[D]. 北京:北京交通大学, 2013. XIN Yue. Research on the decision support system of Guizhou power grid emergency scheduling platform based on ontology knowledge base[D]. Beijing:Beijing Jiaotong University, 2013.