LEADER 04276 am 22006973u 450 001 996418318303316 005 20230125225350.0 010 $a3-030-38081-5 024 7 $a10.1007/978-3-030-38081-6 035 $a(CKB)4900000000505168 035 $a(DE-He213)978-3-030-38081-6 035 $a(MiAaPQ)EBC6111699 035 $a(Au-PeEL)EBL6111699 035 $a(OCoLC)1143625021 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/38740 035 $a(PPN)242844871 035 $a(EXLCZ)994900000000505168 100 $a20200103d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMultiple-Aspect Analysis of Semantic Trajectories$b[electronic resource] $eFirst International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings /$fedited by Konstantinos Tserpes, Chiara Renso, Stan Matwin 205 $a1st ed. 2020. 210 $cSpringer Nature$d2020 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (IX, 133 p. 93 illus., 47 illus. in color.) 225 1 $aLecture Notes in Artificial Intelligence ;$v11889 311 $a3-030-38080-7 327 $aLearning from our Movements - The Mobility Data Analytics Era -- Uncovering hidden concepts from AIS data: A network abstraction of maritime traffic for anomaly detection -- Nowcasting Unemployment Rates with Smartphone GPS data -- Online long-term trajectory prediction based on mined route patterns -- EvolvingClusters: Online Discovery of Group Patterns in Enriched Maritime Data -- Prospective Data Model and Distributed Query Processing for Mobile Sensing Data Streams -- Predicting Fishing Effort and Catch Using Semantic Trajectories and Machine Learning -- A Neighborhood-augmented LSTM Model for Taxi-Passenger Demand Prediction -- Multi-Channel Convolutional Neural Networks for Handling Multi-Dimensional Semantic Trajectories and Predicting Future Semantic Locations. 330 $aThis open access book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019. The 8 full papers presented were carefully reviewed and selected from 12 submissions. They represent an interesting mix of techniques to solve recurrent as well as new problems in the semantic trajectory domain, such as data representation models, data management systems, machine learning approaches for anomaly detection, and common pathways identification. 410 0$aLecture Notes in Artificial Intelligence ;$v11889 606 $aMachine learning 606 $aApplication software 606 $aOptical data processing 606 $aMachine Learning$3https://scigraph.springernature.com/ontologies/product-market-codes/I21010 606 $aComputer Applications$3https://scigraph.springernature.com/ontologies/product-market-codes/I23001 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 610 $aComputer science 610 $aMachine learning 610 $aApplication software 610 $aOptical data processing 615 0$aMachine learning. 615 0$aApplication software. 615 0$aOptical data processing. 615 14$aMachine Learning. 615 24$aComputer Applications. 615 24$aImage Processing and Computer Vision. 676 $a006.31 700 $aTserpes$b Konstantinos$4edt$0330033 702 $aTserpes$b Konstantinos$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRenso$b Chiara$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMatwin$b Stan$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996418318303316 996 $aMultiple-Aspect Analysis of Semantic Trajectories$93358440 997 $aUNISA