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Multi-Domain User-Generated Content Based Model to Enrich Road Network Data for Multi-Criteria Route Planning

机译:基于多域用户生成的基于内容的模型,以丰富道路网络数据,实现多准则路线规划

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摘要

By utilizing today's web-based technologies, people can act as sensors and share their perceptions, emotions and observations in a variety of data forms, such as images, videos, texts, Global Positioning System (GPS) trajectories and maps. These forms are collectively called user-generated content (UGC). These data are in different domains and have a multi-modality nature. Although recent efforts have probed the acquisition of local knowledge by using single-domain UGC data in specific applications, such efforts have not thus far presented a model considering multi-domain UGC specifically to enrich road network data. This article aims at presenting such a model wherein, with the help of each data domain of UGC, one aspect of people knowledge about the road segment is obtained. These different aspects of knowledge are integrated using a Skyline operator to support multi-criteria route finding. We name this model ERSBU (enriching road segments based on UGC). In ERSBU, road segments are basic spatial units, and their subjective properties have been extracted by using available UGC. The scenic score for each road segment was computed by using geo-tagged Panoramio photos. The accessibility level of each road segment to different facilities was calculated based on data captured from Wikimapia and OpenStreetMap. Moreover, for measuring the movement popularity of each road segment, Wikiloc and Everytrail GPS trajectories were utilized. For the implementation of the ERSBU model, Tehran region 6 was considered the case study area. The Evaluation of the results proved that road segments that achieved a high score based on knowledge extracted from UGC also mostly gained top scores by analyzing traditional maps. ERSBU allows users to accomplish more-qualitative path finding by considering the multi-view characteristics of road segments.
机译:通过利用当今基于Web的技术,人们可以充当传感器并以各种数据形式(例如图像,视频,文本,全球定位系统(GPS)轨迹和地图)共享他们的感知,情感和观察结果。这些形式统称为用户生成的内容(UGC)。这些数据位于不同的域中,具有多模式性质。尽管最近的努力已经探究了在特定应用中通过使用单域UGC数据来获取本地知识的方法,但是到目前为止,这种努力还没有提出考虑多域UGC来专门丰富道路网络数据的模型。本文旨在提出一种模型,其中借助UGC的每个数据域,获得人们对路段的了解的一个方面。使用Skyline运营商集成了知识的这些不同方面,以支持多准则路线查找。我们将此模型命名为ERSBU(基于UGC的路段富集)。在ERSBU中,路段是基本的空间单位,其主观属性已通过使用可用的UGC提取。通过使用带有地理标签的Panoramio照片来计算每个路段的风景名胜分数。根据从Wikimapia和OpenStreetMap捕获的数据来计算每个路段对不同设施的可访问性级别。此外,为了测量每个路段的运动受欢迎程度,使用了Wikiloc和Everytrail GPS轨迹。为了实施ERSBU模型,德黑兰6区被视为案例研究区域。结果评估表明,基于从教资会提取的知识获得高分的路段,通过分析传统地图也大多获得了最高分。 ERSBU允许用户通过考虑路段的多视图特征来完成更定性的路径查找。

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  • 来源
    《Geographical analysis》 |2017年第3期|239-267|共29页
  • 作者单位

    KN Toosi Univ Technol, Fac Geodesy & Geomat Engn, Dept Geospatial Informat Syst, Valiasr St, Tehran, Iran;

    KN Toosi Univ Technol, Fac Geodesy & Geomat Engn, Dept Geospatial Informat Syst, Valiasr St, Tehran, Iran;

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