Knowledge-Enriched Route Computation
Knowledge-Enriched Route Computation
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DOI：
10.1007/978-3-319-22363-6_9
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发表时间：
2015-08
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影响因子：
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通讯作者：
Georgios Skoumas;Klaus Arthur Schmid;Gregor Jossé;Matthias Schubert;M. Nascimento;Andreas Züfle;M. Renz-M
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文献类型：
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作者：
Georgios Skoumas;Klaus Arthur Schmid;Gregor Jossé;Matthias Schubert;M. Nascimento;Andreas Züfle;M. Renz-M
通常由导航系统提供的方向和路径通常是考虑绝对度量导出的，例如，在底层道路网络中找到最短或最快的路径。在数字化地理信息（VGI）的帮助下，地理空间信息包含在用户生成的内容中，我们的目标是获得不仅最小化距离而且还导致通过更受欢迎的区域的路径。基于地标在地理信息科学和人类认知中的重要性，我们提取了一种VGI，即定义了兴趣点（POI）对之间的接近性（附近，旁边）的空间关系，并根据概率框架对其进行量化。随后，使用贝叶斯推理，我们得到一个基于人群的接近度的信心得分对POI。我们将此措施应用到相应的道路网络的基础上改变成本函数，它不完全依赖于距离，但也考虑到众包的地理空间信息。最后，我们提出了两个路由算法上丰富的道路网络。为了评估我们的方法，我们使用Flickr照片数据作为受欢迎程度的基本事实。我们的实验结果-基于真实的世界数据集-表明，计算的路径w.r.t.我们的替代成本函数在路径长度方面产生了有竞争力的解决方案，同时还提供了更“流行”的路径，使得路由选择更容易并且为用户提供更多信息。
Directions and paths, as commonly provided by navigation systems, are usually derived considering absolute metrics, e.g., finding the shortest or the fastest path within an underlying road network. With the aid of Volunteered Geographic Information (VGI), i.e., geo-spatial information contained in user generated content, we aim at obtaining paths that do not only minimize distance but also lead through more popular areas. Based on the importance of landmarks in Geographic Information Science and in human cognition, we extract a certain kind of VGI, namely spatial relations that definecloseness(nearby, next to) between pairs ofpoints of interest(POIs), and quantify them following a probabilistic framework. Subsequently, using Bayesian inference we obtain a crowd-basedclosenessconfidence score between pairs of POIs. We apply this measure to the corresponding road network based on an altered cost function which does not exclusively rely on distance but also takes crowdsourced geo-spatial information into account. Finally, we propose two routing algorithms on the enriched road network. To evaluate our approach, we use Flickr photo data as a ground truth for popularity. Our experimental results – based on real world datasets – show that the paths computed w.r.t. our alternative cost function yield competitive solutions in terms of path length while also providing more “popular” paths, making routing easier and more informative for the user.