國立虎尾科技大學 |

Big Data Analytics for Time-Critical Mobility Forecasting = From Raw Data to Trajectory-Oriented Mobility Analytics in the Aviation and Maritime Domains /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Big Data Analytics for Time-Critical Mobility Forecasting/ edited by George A. Vouros, Gennady Andrienko, Christos Doulkeridis, Nikolaos Pelekis, Alexander Artikis, Anne-Laure Jousselme, Cyril Ray, Jose Manuel Cordero, David Scarlatti.
其他題名:	From Raw Data to Trajectory-Oriented Mobility Analytics in the Aviation and Maritime Domains /
其他作者:	Vouros, George A.
面頁冊數:	XXXII, 361 p. 126 illus., 100 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Database management. -
電子資源:	https://doi.org/10.1007/978-3-030-45164-6
ISBN:	9783030451646

Big Data Analytics for Time-Critical Mobility Forecasting = From Raw Data to Trajectory-Oriented Mobility Analytics in the Aviation and Maritime Domains /
Big Data Analytics for Time-Critical Mobility ForecastingFrom Raw Data to Trajectory-Oriented Mobility Analytics in the Aviation and Maritime Domains /[electronic resource] :edited by George A. Vouros, Gennady Andrienko, Christos Doulkeridis, Nikolaos Pelekis, Alexander Artikis, Anne-Laure Jousselme, Cyril Ray, Jose Manuel Cordero, David Scarlatti. - 1st ed. 2020. - XXXII, 361 p. 126 illus., 100 illus. in color.online resource.

Part I: Time Critical Mobility Operations and Data: A Perspective from the Maritime and Aviation Domains -- Mobility Data: A Perspective from the Maritime Domain -- The Perspective on Mobility Data from the Aviation Domain -- Part II: Visual Analytics and Trajectory Detection and Summarization: Exploring Data and Constructing Trajectories -- Visual Analytics in the Aviation and Maritime Domains -- Trajectory Detection and Summarization over Surveillance Data Streams -- Part III: Trajectory Oriented Data Management for Mobility Analytics -- Modeling Mobility Data and Constructing Large Knowledge Graphs to Support Analytics: The datAcron Ontology -- Integrating Data by Discovering Topological and Proximity Relations Among Spatiotemporal Entities -- Distributed Storage of Large Knowledge Graphs with Mobility Data -- Part IV: Analytics Towards Time Critical Mobility Forecasting -- Future Location and Trajectory Prediction -- Event Processing for Maritime Situational Awareness -- Offline Trajectory Analytics -- Part V Big Data Architectures for Time Critical Mobility Forecasting -- The δ Big Data Architecture for Mobility Analytics -- Part VI: Ethical Issues for Time Critical Mobility Analytics -- Ethical Issues in Big Data Analytics for Time Critical Mobility Forecasting.

This book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving entities spread across large geographical areas. It presents state-of-the-art methods for processing, managing, detecting and predicting trajectories and important events related to moving entities, together with advanced visual analytics methods, over multiple heterogeneous, voluminous, fluctuating and noisy data streams from moving entities, correlating them with data from archived data sources expressing e.g. entities’ characteristics, geographical information, mobility patterns, mobility regulations and intentional data. The book is divided into six parts: Part I discusses the motivation and background of mobility forecasting supported by trajectory-oriented analytics, and includes specific problems and challenges in the aviation (air-traffic management) and the maritime domains. Part II focuses on big data quality assessment and processing, and presents novel technologies suitable for mobility analytics components. Next, Part III describes solutions toward processing and managing big spatio-temporal data, particularly enriching data streams and integrating streamed and archival data to provide coherent views of mobility, and storing of integrated mobility data in large distributed knowledge graphs for efficient query-answering. Part IV focuses on mobility analytics methods exploiting (online) processed, synopsized and enriched data streams as well as (offline) integrated, archived mobility data, and highlights future location and trajectory prediction methods, distinguishing between short-term and more challenging long-term predictions. Part V examines how methods addressing data management, data processing and mobility analytics are integrated in big data architectures with distinctive characteristics compared to other known big data paradigmatic architectures. Lastly, Part VI covers important ethical issues that research on mobility analytics should address. Providing novel approaches and methodologies related to mobility detection and forecasting needs based on big data exploration, processing, storage, and analysis, this book will appeal to computer scientists and stakeholders in various application domains.

ISBN: 9783030451646

Standard No.: 10.1007/978-3-030-45164-6doiSubjects--Topical Terms:

557799
Database management.

LC Class. No.: QA76.9.D3

Dewey Class. No.: 005.74

Big Data Analytics for Time-Critical Mobility Forecasting = From Raw Data to Trajectory-Oriented Mobility Analytics in the Aviation and Maritime Domains /
LDR:05208nam a22004095i 4500 001 1020400
003 DE-He213
005 20200706091249.0
007 cr nn 008mamaa
008 210318s2020 gw | s |||| 0|eng d
020 $a 9783030451646 $9 978-3-030-45164-6
024 7 $a 10.1007/978-3-030-45164-6 $2 doi
035 $a 978-3-030-45164-6
050 4 $a QA76.9.D3
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
072 7 $a UMT $2 thema
082 0 4 $a 005.74 $2 23
245 1 0 $a Big Data Analytics for Time-Critical Mobility Forecasting $h [electronic resource] : $b From Raw Data to Trajectory-Oriented Mobility Analytics in the Aviation and Maritime Domains / $c edited by George A. Vouros, Gennady Andrienko, Christos Doulkeridis, Nikolaos Pelekis, Alexander Artikis, Anne-Laure Jousselme, Cyril Ray, Jose Manuel Cordero, David Scarlatti.
250 $a 1st ed. 2020.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a XXXII, 361 p. 126 illus., 100 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Part I: Time Critical Mobility Operations and Data: A Perspective from the Maritime and Aviation Domains -- Mobility Data: A Perspective from the Maritime Domain -- The Perspective on Mobility Data from the Aviation Domain -- Part II: Visual Analytics and Trajectory Detection and Summarization: Exploring Data and Constructing Trajectories -- Visual Analytics in the Aviation and Maritime Domains -- Trajectory Detection and Summarization over Surveillance Data Streams -- Part III: Trajectory Oriented Data Management for Mobility Analytics -- Modeling Mobility Data and Constructing Large Knowledge Graphs to Support Analytics: The datAcron Ontology -- Integrating Data by Discovering Topological and Proximity Relations Among Spatiotemporal Entities -- Distributed Storage of Large Knowledge Graphs with Mobility Data -- Part IV: Analytics Towards Time Critical Mobility Forecasting -- Future Location and Trajectory Prediction -- Event Processing for Maritime Situational Awareness -- Offline Trajectory Analytics -- Part V Big Data Architectures for Time Critical Mobility Forecasting -- The δ Big Data Architecture for Mobility Analytics -- Part VI: Ethical Issues for Time Critical Mobility Analytics -- Ethical Issues in Big Data Analytics for Time Critical Mobility Forecasting.
520 $a This book provides detailed descriptions of big data solutions for activity detection and forecasting of very large numbers of moving entities spread across large geographical areas. It presents state-of-the-art methods for processing, managing, detecting and predicting trajectories and important events related to moving entities, together with advanced visual analytics methods, over multiple heterogeneous, voluminous, fluctuating and noisy data streams from moving entities, correlating them with data from archived data sources expressing e.g. entities’ characteristics, geographical information, mobility patterns, mobility regulations and intentional data. The book is divided into six parts: Part I discusses the motivation and background of mobility forecasting supported by trajectory-oriented analytics, and includes specific problems and challenges in the aviation (air-traffic management) and the maritime domains. Part II focuses on big data quality assessment and processing, and presents novel technologies suitable for mobility analytics components. Next, Part III describes solutions toward processing and managing big spatio-temporal data, particularly enriching data streams and integrating streamed and archival data to provide coherent views of mobility, and storing of integrated mobility data in large distributed knowledge graphs for efficient query-answering. Part IV focuses on mobility analytics methods exploiting (online) processed, synopsized and enriched data streams as well as (offline) integrated, archived mobility data, and highlights future location and trajectory prediction methods, distinguishing between short-term and more challenging long-term predictions. Part V examines how methods addressing data management, data processing and mobility analytics are integrated in big data architectures with distinctive characteristics compared to other known big data paradigmatic architectures. Lastly, Part VI covers important ethical issues that research on mobility analytics should address. Providing novel approaches and methodologies related to mobility detection and forecasting needs based on big data exploration, processing, storage, and analysis, this book will appeal to computer scientists and stakeholders in various application domains.
650 0 $a Database management. $3 557799
650 0 $a Mathematical statistics. $3 527941
650 0 $a Transportation engineering. $3 633205
650 0 $a Traffic engineering. $3 639529
650 1 4 $a Database Management. $3 669820
650 2 4 $a Probability and Statistics in Computer Science. $3 669886
650 2 4 $a Transportation Technology and Traffic Engineering. $3 1069531
700 1 $a Vouros, George A. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 894736
700 1 $a Andrienko, Gennady. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1078484
700 1 $a Doulkeridis, Christos. $e editor. $1 https://orcid.org/0000-0002-3219-0510 $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1287196
700 1 $a Pelekis, Nikolaos. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1315866
700 1 $a Artikis, Alexander. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 682701
700 1 $a Jousselme, Anne-Laure. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1315867
700 1 $a Ray, Cyril. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 683603
700 1 $a Cordero, Jose Manuel. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1315868
700 1 $a Scarlatti, David. $e editor. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1315869
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030451639
776 0 8 $i Printed edition: $z 9783030451653
776 0 8 $i Printed edition: $z 9783030451660
856 4 0 $u https://doi.org/10.1007/978-3-030-45164-6
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)