東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Mobility data science = from data to...

Sakr, Mahmoud.

FindBook

Google Book

Amazon

博客來

Mobility data science = from data to insights /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mobility data science/ by Mahmoud Sakr, Alejandro Vaisman, Esteban Zimányi.
其他題名:	from data to insights /
作者:	Sakr, Mahmoud.
其他作者:	Vaisman, Alejandro.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	xxii, 592 p. :ill. (some col.), digital ;24 cm.
內容註:	Preface -- Part I Fundamental Concepts 1 Mobility Data Science 2 Spatial, Temporal, and Mobility Databases 3 Mobility Data Representation 4 Mobility Data Visualization 5 Querying Mobility Databases -- Part II Advanced Topics 6 Query Processing and Indexing 7 Mobility Data Warehouses 8 Distributed Mobility Databases -- Part III Mobility Analytics 9 Mobility Data Cleaning 10 Mobility Data Analysis 11 Urban Mobility Use Case 12 Concluding Remarks.
Contained By:	Springer Nature eBook
標題:	Data mining. -
電子資源:	https://doi.org/10.1007/978-3-031-82636-8
ISBN:	9783031826368

Mobility data science = from data to insights /
Sakr, Mahmoud.

Mobility data sciencefrom data to insights /[electronic resource] :by Mahmoud Sakr, Alejandro Vaisman, Esteban Zimányi. - Cham :Springer Nature Switzerland :2025. - xxii, 592 p. :ill. (some col.), digital ;24 cm. - Data-centric systems and applications,2197-974X. - Data-centric systems and applications..

Preface -- Part I Fundamental Concepts 1 Mobility Data Science 2 Spatial, Temporal, and Mobility Databases 3 Mobility Data Representation 4 Mobility Data Visualization 5 Querying Mobility Databases -- Part II Advanced Topics 6 Query Processing and Indexing 7 Mobility Data Warehouses 8 Distributed Mobility Databases -- Part III Mobility Analytics 9 Mobility Data Cleaning 10 Mobility Data Analysis 11 Urban Mobility Use Case 12 Concluding Remarks.

This textbook covers the key topics in mobility data analysis, including all steps of the data science pipeline illustrated with real-world examples. The book is composed of three parts. Part I "Fundamental Concepts" provides the background for this book by introducing spatial and temporal databases and motivating the need for mobility databases. Further chapters in this part are devoted to a formal model for representing mobility data, an introduction to mobility data visualization, and the topic of querying mobility databases. Part II "Advanced Topics" covers topics such as query processing and indexing, illustrated with PostgreSQL, introduces mobility data warehouses using synthetic data, and concludes with distributed mobility databases. Part III "Mobility Analytics" covers important topics like mobility data cleaning, including the identification of erroneous data, and mobility analysis using foundational algorithms for spatial and mobility data. It also includes an urban mobility use case that illustrates the concepts presented throughout the book in a real application setting. This textbook is written for undergraduate and graduate computer science courses on mobility data science. As such, it follows a pedagogical style to make the work of the instructor easier and to help students to understand the concepts being delivered, complementing the presentation with exercises and a companion GitHub repository. SQL is used as a high-level language for analytics, allowing students to write complex data science code, while abstracting away implementation details. Researchers and practitioners who are interested in an introduction to the area of mobility data science will also find the book a useful reference.

ISBN: 9783031826368

Standard No.: 10.1007/978-3-031-82636-8doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA746.9.D343

Dewey Class. No.: 006.312

Mobility data science = from data to insights /
LDR:03262nmm a2200337 a 4500 001 2409664
003 DE-He213
005 20250409152724.0
006 m d
007 cr nn 008maaau
008 260204s2025 sz s 0 eng d
020 $a 9783031826368 $q (electronic bk.)
020 $a 9783031826351 $q (paper)
024 7 $a 10.1007/978-3-031-82636-8 $2 doi
035 $a 978-3-031-82636-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA746.9.D343
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 006.312 $2 23
090 $a QA746.9.D343 $b S158 2025
100 1 $a Sakr, Mahmoud. $3 2183158
245 1 0 $a Mobility data science $h [electronic resource] : $b from data to insights / $c by Mahmoud Sakr, Alejandro Vaisman, Esteban Zimányi.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a xxii, 592 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Data-centric systems and applications, $x 2197-974X
505 0 $a Preface -- Part I Fundamental Concepts 1 Mobility Data Science 2 Spatial, Temporal, and Mobility Databases 3 Mobility Data Representation 4 Mobility Data Visualization 5 Querying Mobility Databases -- Part II Advanced Topics 6 Query Processing and Indexing 7 Mobility Data Warehouses 8 Distributed Mobility Databases -- Part III Mobility Analytics 9 Mobility Data Cleaning 10 Mobility Data Analysis 11 Urban Mobility Use Case 12 Concluding Remarks.
520 $a This textbook covers the key topics in mobility data analysis, including all steps of the data science pipeline illustrated with real-world examples. The book is composed of three parts. Part I "Fundamental Concepts" provides the background for this book by introducing spatial and temporal databases and motivating the need for mobility databases. Further chapters in this part are devoted to a formal model for representing mobility data, an introduction to mobility data visualization, and the topic of querying mobility databases. Part II "Advanced Topics" covers topics such as query processing and indexing, illustrated with PostgreSQL, introduces mobility data warehouses using synthetic data, and concludes with distributed mobility databases. Part III "Mobility Analytics" covers important topics like mobility data cleaning, including the identification of erroneous data, and mobility analysis using foundational algorithms for spatial and mobility data. It also includes an urban mobility use case that illustrates the concepts presented throughout the book in a real application setting. This textbook is written for undergraduate and graduate computer science courses on mobility data science. As such, it follows a pedagogical style to make the work of the instructor easier and to help students to understand the concepts being delivered, complementing the presentation with exercises and a companion GitHub repository. SQL is used as a high-level language for analytics, allowing students to write complex data science code, while abstracting away implementation details. Researchers and practitioners who are interested in an introduction to the area of mobility data science will also find the book a useful reference.
650 0 $a Data mining. $3 562972
650 0 $a Geodatabases. $3 603971
650 0 $a Database management. $3 527442
650 1 4 $a Data Science. $3 3538937
650 2 4 $a Database Management System. $3 3591759
650 2 4 $a Geographical Information System. $3 3538564
700 1 $a Vaisman, Alejandro. $3 2106796
700 1 $a Zimányi, Esteban. $3 3782978
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Data-centric systems and applications. $3 1619753
856 4 0 $u https://doi.org/10.1007/978-3-031-82636-8
950 $a Computer Science (SpringerNature-11645)