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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| Médium: | E-kniha |
| Jazyk: | angličtina |
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Cham
Springer Nature
2020
Springer International Publishing AG Springer Open |
| Vydání: | 1 |
| Edice: | Lecture Notes in Artificial Intelligence |
| Témata: | |
| ISBN: | 9783030380816, 3030380815, 9783030380809, 3030380807 |
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- 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