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Titlebook: Multiple-Aspect Analysis of Semantic Trajectories; First International Konstantinos Tserpes,Chiara Renso,Stan Matwin Conference proceeding

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書目名稱Multiple-Aspect Analysis of Semantic Trajectories
副標(biāo)題First International
編輯Konstantinos Tserpes,Chiara Renso,Stan Matwin
視頻videohttp://file.papertrans.cn/642/641061/641061.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Multiple-Aspect Analysis of Semantic Trajectories; First International  Konstantinos Tserpes,Chiara Renso,Stan Matwin Conference proceeding
描述.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..
出版日期Conference proceedings‘‘‘‘‘‘‘‘ 2020
關(guān)鍵詞Open Access; artificial intelligence; communication systems; computer vision; correlation analysis; data
版次1
doihttps://doi.org/10.1007/978-3-030-38081-6
isbn_softcover978-3-030-38080-9
isbn_ebook978-3-030-38081-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s) 2020
The information of publication is updating

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0302-9743 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 r
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978-3-030-38080-9The Editor(s) (if applicable) and The Author(s) 2020
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https://doi.org/10.1007/978-3-030-38081-6Open Access; artificial intelligence; communication systems; computer vision; correlation analysis; data
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