Multiple-Aspect Analysis of Semantic Trajectories First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings
This open access book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD...
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| Main Authors | , , |
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| Format | eBook |
| Language | English |
| Published |
Cham
Springer Nature
2020
Springer International Publishing AG Springer Open |
| Edition | 1 |
| Series | Lecture Notes in Artificial Intelligence |
| Subjects | |
| Online Access | Get full text |
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| Abstract | This open access book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019.The 8 full papers presented were carefully reviewed and selected from 12 submissions. They represent an interesting mix of techniques to solve recurrent as well as new problems in the semantic trajectory domain, such as data representation models, data management systems, machine learning approaches for anomaly detection, and common pathways identification. |
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| AbstractList | This open access book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019.The 8 full papers presented were carefully reviewed and selected from 12 submissions. They represent an interesting mix of techniques to solve recurrent as well as new problems in the semantic trajectory domain, such as data representation models, data management systems, machine learning approaches for anomaly detection, and common pathways identification. |
| Author | Renso, Chiara Tserpes, Konstantinos Matwin, Stan |
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| Editor | Renso, Chiara Matwin, Stan Tserpes, Konstantinos |
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| PublicationSeriesTitle | Lecture Notes in Artificial Intelligence |
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| Snippet | This open access book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic... |
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| Subtitle | First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings |
| TableOfContents | Intro -- Preface -- Organization -- Contents -- Learning from Our Movements - The Mobility Data Analytics Era -- 1 Introduction -- 2 Flashback to the Past -- 3 Nowadays - Mobility Data Analytics -- 4 What's Next -- References -- Uncovering Hidden Concepts from AIS Data: A Network Abstraction of Maritime Traffic for Anomaly Detection -- 1 Introduction -- 2 Related Work -- 3 The Proposed Approach -- 3.1 Route Identification -- 3.2 Trajectory Clustering -- 3.3 Enriched Network Abstraction -- 4 Application to a Real Dataset -- 4.1 Network Creation from Real AIS Positions -- 4.2 Detection of Outliers in the Trajectories -- 5 Conclusion and Future Steps -- References -- Nowcasting Unemployment Rates with Smartphone GPS Data -- 1 Introduction -- 2 Related Works -- 3 Data -- 3.1 The Unemployment Rate -- 3.2 The GPS Data -- 4 Nowcasting Model -- 4.1 The MIDAS Model -- 4.2 Estimation of Parameters -- 4.3 Imputation of Missing Data -- 4.4 Feature Selection -- 5 Evaluation -- 5.1 Nowcast for the Number of Unemployed Persons -- 5.2 Forecasts for Unemployment Rates -- 6 Conclusion -- References -- Online Long-Term Trajectory Prediction Based on Mined Route Patterns -- 1 Introduction -- 2 Background -- 3 Overview of the Approach -- 4 Methodology -- 4.1 Offline Step: Mobility Pattern Extraction Based on Sub-trajectory Clustering -- 4.2 Online Step: On Long-Term Future Location Prediction -- 5 Experimental Evaluation -- 5.1 Experimental Setup -- 5.2 Results -- 6 Conclusion -- References -- EvolvingClusters: Online Discovery of Group Patterns in Enriched Maritime Data -- 1 Introduction -- 2 Background Knowledge and Related Work -- 3 Problem Formulation -- 3.1 Problem Definition -- 3.2 What Is Special About Maritime Data -- 4 The EvolvingClusters Algorithm -- 5 Experimental Study -- 5.1 Dataset Preparation -- 5.2 Preliminary Results -- 6 Conclusions and Future Work References -- Prospective Data Model and Distributed Query Processing for Mobile Sensing Data Streams -- 1 Introduction -- 2 Challenges of STDS Management -- 3 Related Work -- 3.1 Offline Processing of STDS -- 3.2 Online Processing of STDS -- 3.3 Unified Approach for STDS Management -- 4 System Overview -- 5 Data Model -- 5.1 Preliminaries -- 5.2 Logical Data Model -- 5.3 Physical Data Model -- 6 Query Processing -- 7 Conclusion -- References -- Predicting Fishing Effort and Catch Using Semantic Trajectories and Machine Learning -- 1 Introduction -- 2 Related Works -- 2.1 Data Fusion of Sea Data and Semantic Trajectories -- 2.2 Fishing Activities Forecast -- 3 A Framework for Predicting CPUE -- 3.1 Data Sources -- 3.2 Data Fusion and Semantic Modeling -- 3.3 Predictive Modeling -- 4 Experiments and Results -- 5 Conclusion and Future Work -- References -- A Neighborhood-Augmented LSTM Model for Taxi-Passenger Demand Prediction -- 1 Introduction -- 2 Related Work -- 3 Neighborhood-Augmented Taxi Demand Prediction -- 3.1 Problem Definition -- 3.2 Neighborhood-Augmented LSTM Model -- 4 Experimental Evaluation -- 4.1 Dataset -- 4.2 Experimental Setup and Evaluation Measures -- 4.3 Baselines and Method Parameter Settings -- 4.4 LSTM Parameter Settings -- 4.5 Taxi-Demand Prediction Quality Results -- 4.6 Impact of Neighborhood -- 5 Conclusions and Outlook -- References -- Multi-channel Convolutional Neural Networks for Handling Multi-dimensional Semantic Trajectories and Predicting Future Semantic Locations -- 1 Introduction -- 2 Related Work -- 3 Semantic Trajectories -- 4 Multi-channel Convolutional Neural Networks on Semantic Trajectories -- 5 Evaluation -- 6 Conclusion -- References -- Author Index |
| Title | Multiple-Aspect Analysis of Semantic Trajectories |
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