| 多源道路智能选取的本体知识推理方法EI北大核心CSCD |
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| 引用本文： | 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EI北大核心CSCD[J].测绘学报,2022,51(2):279-289. |
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| 作者姓名： | 郭漩 钱海忠 王骁 刘俊楠 任琰 赵钰哲 陈国庆 |
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| 作者单位： | 1. 信息工程大学地理空间信息学院, 河南 郑州 450000;2. 信息工程大学数据目标与工程学院, 河南 郑州 450000 |
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| 基金项目： | 国家自然科学基金(41571442)；;河南省杰出青年科学基金(212300410014)； |
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| 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。
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| 关 键 词： | 道路选取 多源数据 本体 相似性 语义网规则语言 |
| 收稿时间： | 2021-04-02 |
| 修稿时间： | 2021-06-08 |
Ontology knowledge reasoning method for multi-source intelligent road selection |
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| 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. |
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| Authors: | GUO Xuan QIAN Haizhong WANG Xiao LIU Junnan REN Yan ZHAO Yuzhe CHEN Guoqing |
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| Institution: | 1. Institute of Geospatial Information, Information Engineering University, Zhengzhou 450000, China;2. Institute of Data and Target Engineering, Information Engineering University, Zhengzhou 450000, China |
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| 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. |
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| Keywords: | road selection multi-source data ontology similarity semantic web rule language |
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