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Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data最新文献

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A Repository of Network-Constrained Trajectory Data (Position Paper) 网络约束轨迹数据库(意见书)
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data Pub Date : 2019-11-05 DOI: 10.1145/3356392.3365219
S. Funke, Sabine Storandt
{"title":"A Repository of Network-Constrained Trajectory Data (Position Paper)","authors":"S. Funke, Sabine Storandt","doi":"10.1145/3356392.3365219","DOIUrl":"https://doi.org/10.1145/3356392.3365219","url":null,"abstract":"We propose the creation of a repository which collects and makes available network-constrained trajectory data. The repository should become a central instance for researchers who want to work with network-constrained trajectory data on a large scale, allowing for efficient filtering and export of selected trajectories based on spatial, temporal and semantic attributes.","PeriodicalId":415844,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128619548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Understanding Movement in Context with Heterogeneous Data 在异构数据的背景下理解运动
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data Pub Date : 2019-11-05 DOI: 10.1145/3356392.3365222
O. Derin, A. Mitra, Matei Stroila, B. Custers, Wouter Meulemans, Marcel Roeloffzen, Kevin Verbeek
{"title":"Understanding Movement in Context with Heterogeneous Data","authors":"O. Derin, A. Mitra, Matei Stroila, B. Custers, Wouter Meulemans, Marcel Roeloffzen, Kevin Verbeek","doi":"10.1145/3356392.3365222","DOIUrl":"https://doi.org/10.1145/3356392.3365222","url":null,"abstract":"Movement data, as captured by myriad sensors, has been growing exponentially. Hence, multidisciplinary approaches for analyzing movement has become feasible. Though, movement pertains to a large variety of domains and applications, the focus of this position paper is understanding human movement (mobility) in various forms. We position maps as heterogeneous, multidimensional and digital representation of reality and advocate their role in contextualizing movement. We overview the main problems for analyzing human mobility with special attention to movement in context, leveraging heterogeneous data. We review the state-of-the-art in solving these problems and describe remaining open problems and challenges for future work. Finally, we offer a view of existing as well as future mapping and location services that could enable these.","PeriodicalId":415844,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121027559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Location Graphs for Movement Data Modeling, Analytics and Visualization 用于运动数据建模、分析和可视化的位置图
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data Pub Date : 2019-11-05 DOI: 10.1145/3356392.3365223
C. Barnes
{"title":"Location Graphs for Movement Data Modeling, Analytics and Visualization","authors":"C. Barnes","doi":"10.1145/3356392.3365223","DOIUrl":"https://doi.org/10.1145/3356392.3365223","url":null,"abstract":"Modeling movement through an environment can be a complicated task given the variations of data scale, quality, temporal sampling, and fidelity of location information. We present recent work in modeling location information both spatially, temporally and semantically using a new product called Location Graph.","PeriodicalId":415844,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129253050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Latent Terrain Representations for Trajectory Prediction 用于轨迹预测的潜在地形表示
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data Pub Date : 2019-11-05 DOI: 10.1145/3356392.3365218
Andrew W. Feng, A. Gordon
{"title":"Latent Terrain Representations for Trajectory Prediction","authors":"Andrew W. Feng, A. Gordon","doi":"10.1145/3356392.3365218","DOIUrl":"https://doi.org/10.1145/3356392.3365218","url":null,"abstract":"In natural outdoor environments, the shape of the surface terrain is an important factor in selecting a traversal path, both when operating off-road vehicles and maneuvering on foot. With the increased availability of digital elevation models for outdoor terrain, new opportunities exist to exploit this contextual information to improve automated path prediction. In this paper, we investigate predictive neural network models for outdoor trajectories that traverse terrain with known surface topography. We describe a method of encoding digital surface models as vectors in latent space using Wasserstein Autoencoders, and their use in convolutional neural networks that predict future trajectory positions from past trajectory data. We observe gains in predictive performance across three experiments, using both synthetic and recorded trajectories on real-world terrain.","PeriodicalId":415844,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125444572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Shared micro-mobility patterns as measures of city similarity: Position Paper 共享微移动模式作为城市相似性的度量:立场文件
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data Pub Date : 2019-11-05 DOI: 10.1145/3356392.3365221
Grant McKenzie
{"title":"Shared micro-mobility patterns as measures of city similarity: Position Paper","authors":"Grant McKenzie","doi":"10.1145/3356392.3365221","DOIUrl":"https://doi.org/10.1145/3356392.3365221","url":null,"abstract":"Micro-mobility services, such as dockless e-scooters and e-bikes, are inundating urban centers around the world. The mass adoption of these services, and ubiquity of the companies operating them, offer a unique opportunity through which to compare cities. In this position paper, a series of spatiotemporal measures are proposed based on activity data collected from shared micro-mobility services. The purpose of this paper is to identify a number of ways that these new mobility services can serve to augment existing city similarity approaches.","PeriodicalId":415844,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127334033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Inferring Semantically Enriched Representative Trajectories 推理语义丰富的代表性轨迹
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data Pub Date : 2019-11-05 DOI: 10.1145/3356392.3365220
Jana Seep, J. Vahrenhold
{"title":"Inferring Semantically Enriched Representative Trajectories","authors":"Jana Seep, J. Vahrenhold","doi":"10.1145/3356392.3365220","DOIUrl":"https://doi.org/10.1145/3356392.3365220","url":null,"abstract":"In the analysis and visualisation of clustered spatial trajectories, the computation of a representative trajectory for a given cluster of data trajectories plays an important role. Usually, such a representative trajectory is computed based upon the data trajectories' spatial characteristics only, e. g., as an average, median, or central trajectory. However, in many cases, the input data is enriched by various types of semantic information which may document characteristics of the trajectories as well. We present an approach to inferring representative trajectories for a given cluster of trajectories. Our approach constructs an extended finite state machine describing the spatial and non-spatial properties of the data trajectories in a given cluster. This extended finite state machine then can be used to generate a representative trajectory exhibiting characteristic changes in spatial and non-spatial properties. The extended finite state machine constructed is annotated with these changes, hence enabling domain experts to further analyse and assess the constructed representative trajectory.","PeriodicalId":415844,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117094555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data 第一届ACM SIGSPATIAL国际研讨会论文集:多面运动数据计算
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data Pub Date : 1900-01-01 DOI: 10.1145/3356392
{"title":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data","authors":"","doi":"10.1145/3356392","DOIUrl":"https://doi.org/10.1145/3356392","url":null,"abstract":"","PeriodicalId":415844,"journal":{"name":"Proceedings of the 1st ACM SIGSPATIAL International Workshop on Computing with Multifaceted Movement Data","volume":"104 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113960451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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