Multiple-Aspect Analysis of Semantic Trajectories First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, W?rzburg, Germany, September 16, 2019, Proceedings
Language: English
Published by Springer, 2020
- Softcover
- New
Condition: New
£ 57.55
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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 W?rzburg, 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. Sprache: Englisch Gewicht in Gramm: 230.
Seller Inventory # IB-201955
- Title
- Multiple-Aspect Analysis of Semantic Trajectories First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, W?rzburg, Germany, September 16, 2019, Proceedings
- Publisher
- Springer
- Publication year
- 2020
- Condition
- Neu
- Binding
- Softcover/Taschenbuch
- Language
- English
- ISBN 10
- 3030380807
- ISBN 13
- 9783030380809
- Item weight
- 230 grams
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.
"Synopsis" may belong to another edition of this title.
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"About the title" may belong to another edition of this title.
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