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dc.contributor.editorTserpes, Konstantinos
dc.contributor.editorRenso, Chiara
dc.contributor.editorMatwin, Stan
dc.date.accessioned2020-03-18 13:36:15
dc.date.accessioned2020-04-01T09:11:21Z
dc.date.available2020-04-01T09:11:21Z
dc.date.issued2020
dc.identifier1006836
dc.identifier.urihttp://library.oapen.org/handle/20.500.12657/23319
dc.description.abstractThis 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.
dc.languageEnglish
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UB Information technology: general topicsen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence::UYQM Machine learningen_US
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science::UYT Image processingen_US
dc.subject.otherComputer science
dc.subject.otherMachine learning
dc.subject.otherApplication software
dc.subject.otherOptical data processing
dc.titleMultiple-Aspect Analysis of Semantic Trajectories
dc.title.alternativeFirst International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings
dc.typebook
oapen.identifier.doi10.1007/978-3-030-38081-6
oapen.relation.isPublishedBy6c6992af-b843-4f46-859c-f6e9998e40d5
oapen.pages133


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