Language:
English
繁體中文
Help
圖資館首頁
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Spatio-temporal data streams
~
Galic, Zdravko.
Spatio-temporal data streams
Record Type:
Electronic resources : Monograph/item
Title/Author:
Spatio-temporal data streamsby Zdravko Galic.
Author:
Galic, Zdravko.
Published:
New York, NY :Springer New York :2016.
Description:
xiv, 107 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Streaming technology (Telecommunications)Management.
Online resource:
http://dx.doi.org/10.1007/978-1-4939-6575-5
ISBN:
9781493965755$q(electronic bk.)
Spatio-temporal data streams
Galic, Zdravko.
Spatio-temporal data streams
[electronic resource] /by Zdravko Galic. - New York, NY :Springer New York :2016. - xiv, 107 p. :ill., digital ;24 cm. - SpringerBriefs in computer science,2191-5768. - SpringerBriefs in computer science..
Introduction -- Spatio-Temporal Continuous Queries -- Spatio-Temporal Data Streams and Big Data Paradigm -- Spatio-Temporal Data Stream Clustering.
This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.
ISBN: 9781493965755$q(electronic bk.)
Standard No.: 10.1007/978-1-4939-6575-5doiSubjects--Topical Terms:
758179
Streaming technology (Telecommunications)
--Management.
LC Class. No.: TK5105.386
Dewey Class. No.: 006.7876
Spatio-temporal data streams
LDR
:02309nmm a2200337 a 4500
001
495952
003
DE-He213
005
20160826142123.0
006
m d
007
cr nn 008maaau
008
170323s2016 nyu s 0 eng d
020
$a
9781493965755$q(electronic bk.)
020
$a
9781493965731$q(paper)
024
7
$a
10.1007/978-1-4939-6575-5
$2
doi
035
$a
978-1-4939-6575-5
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TK5105.386
072
7
$a
UN
$2
bicssc
072
7
$a
UMT
$2
bicssc
072
7
$a
COM021000
$2
bisacsh
082
0 4
$a
006.7876
$2
23
090
$a
TK5105.386
$b
.G156 2016
100
1
$a
Galic, Zdravko.
$3
758178
245
1 0
$a
Spatio-temporal data streams
$h
[electronic resource] /
$c
by Zdravko Galic.
260
$a
New York, NY :
$b
Springer New York :
$b
Imprint: Springer,
$c
2016.
300
$a
xiv, 107 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
SpringerBriefs in computer science,
$x
2191-5768
505
0
$a
Introduction -- Spatio-Temporal Continuous Queries -- Spatio-Temporal Data Streams and Big Data Paradigm -- Spatio-Temporal Data Stream Clustering.
520
$a
This SpringerBrief presents the fundamental concepts of a specialized class of data stream, spatio-temporal data streams, and demonstrates their distributed processing using Big Data frameworks and platforms. It explores a consistent framework which facilitates a thorough understanding of all different facets of the technology, from basic definitions to state-of-the-art techniques. Key topics include spatio-temporal continuous queries, distributed stream processing, SQL-like language embedding, and trajectory stream clustering. Over the course of the book, the reader will become familiar with spatio-temporal data streams management and data flow processing, which enables the analysis of huge volumes of location-aware continuous data streams. Applications range from mobile object tracking and real-time intelligent transportation systems to traffic monitoring and complex event processing. Spatio-Temporal Data Streams is a valuable resource for researchers studying spatio-temporal data streams and Big Data analytics, as well as data engineers and data scientists solving data management and analytics problems associated with this class of data.
650
0
$a
Streaming technology (Telecommunications)
$x
Management.
$3
758179
650
0
$a
Data mining.
$3
184440
650
1 4
$a
Computer Science.
$3
212513
650
2 4
$a
Database Management.
$3
273994
650
2 4
$a
Geographical Information Systems/Cartography.
$3
273999
650
2 4
$a
Computer Communication Networks.
$3
218087
650
2 4
$a
Graph Theory.
$3
522732
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
830
0
$a
SpringerBriefs in computer science.
$3
559641
856
4 0
$u
http://dx.doi.org/10.1007/978-1-4939-6575-5
950
$a
Computer Science (Springer-11645)
based on 0 review(s)
ALL
電子館藏
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
000000132303
電子館藏
1圖書
電子書
EB TK5105.386 G156 2016
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Multimedia file
http://dx.doi.org/10.1007/978-1-4939-6575-5
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login