語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Analyzing time interval dataintroduc...
~
Meisen, Philipp.
Analyzing time interval dataintroducing an information system for time interval data analysis /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Analyzing time interval databy Philipp Meisen.
其他題名:
introducing an information system for time interval data analysis /
作者:
Meisen, Philipp.
出版者:
Wiesbaden :Springer Fachmedien Wiesbaden :2016.
面頁冊數:
xxxi, 232 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
System analysisData processing.
電子資源:
http://dx.doi.org/10.1007/978-3-658-15728-9
ISBN:
9783658157289$q(electronic bk.)
Analyzing time interval dataintroducing an information system for time interval data analysis /
Meisen, Philipp.
Analyzing time interval data
introducing an information system for time interval data analysis /[electronic resource] :by Philipp Meisen. - Wiesbaden :Springer Fachmedien Wiesbaden :2016. - xxxi, 232 p. :ill., digital ;24 cm.
Modeling Time Interval Data -- Querying for Time Interval Data -- Similarity of Time Interval Data -- An Information System for Time Interval Data Analysis.
Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding any type of summarizability problems), providing insights, and visualizing results processing millions of intervals within milliseconds using an intuitive SQL-based query language. The heart of the solution is based on several bitmap-based indexes, which enable the system to handle huge amounts of time interval data. Contents Modeling Time Interval Data Querying for Time Interval Data Similarity of Time Interval Data An Information System for Time Interval Data Analysis Target Groups Researchers and students in the field of information management Business analysts and dispatchers in the fields of online analytical processing (OLAP), data warehousing (DW), business intelligence (BI), workforce management, and data science The Author Philipp Meisen holds a doctoral degree from RWTH Aachen, where he was a research group leader at the Chair of Information Management in Mechanical Engineering.
ISBN: 9783658157289$q(electronic bk.)
Standard No.: 10.1007/978-3-658-15728-9doiSubjects--Topical Terms:
182728
System analysis
--Data processing.
LC Class. No.: QA402
Dewey Class. No.: 519.5
Analyzing time interval dataintroducing an information system for time interval data analysis /
LDR
:02336nmm a2200325 a 4500
001
497307
003
DE-He213
005
20160913110619.0
006
m d
007
cr nn 008maaau
008
170420s2016 gw s 0 eng d
020
$a
9783658157289$q(electronic bk.)
020
$a
9783658157272$q(paper)
024
7
$a
10.1007/978-3-658-15728-9
$2
doi
035
$a
978-3-658-15728-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA402
072
7
$a
UT
$2
bicssc
072
7
$a
COM069000
$2
bisacsh
072
7
$a
COM032000
$2
bisacsh
082
0 4
$a
519.5
$2
23
090
$a
QA402
$b
.M515 2016
100
1
$a
Meisen, Philipp.
$3
759916
245
1 0
$a
Analyzing time interval data
$h
[electronic resource] :
$b
introducing an information system for time interval data analysis /
$c
by Philipp Meisen.
260
$a
Wiesbaden :
$b
Springer Fachmedien Wiesbaden :
$b
Imprint: Springer Vieweg,
$c
2016.
300
$a
xxxi, 232 p. :
$b
ill., digital ;
$c
24 cm.
505
0
$a
Modeling Time Interval Data -- Querying for Time Interval Data -- Similarity of Time Interval Data -- An Information System for Time Interval Data Analysis.
520
$a
Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding any type of summarizability problems), providing insights, and visualizing results processing millions of intervals within milliseconds using an intuitive SQL-based query language. The heart of the solution is based on several bitmap-based indexes, which enable the system to handle huge amounts of time interval data. Contents Modeling Time Interval Data Querying for Time Interval Data Similarity of Time Interval Data An Information System for Time Interval Data Analysis Target Groups Researchers and students in the field of information management Business analysts and dispatchers in the fields of online analytical processing (OLAP), data warehousing (DW), business intelligence (BI), workforce management, and data science The Author Philipp Meisen holds a doctoral degree from RWTH Aachen, where he was a research group leader at the Chair of Information Management in Mechanical Engineering.
650
0
$a
System analysis
$x
Data processing.
$3
182728
650
0
$a
Time.
$3
178353
650
1 4
$a
Computer Science.
$3
212513
650
2 4
$a
Information Systems and Communication Service.
$3
274025
650
2 4
$a
Data Structures, Cryptology and Information Theory.
$3
273993
650
2 4
$a
Software Engineering/Programming and Operating Systems.
$3
273711
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-3-658-15728-9
950
$a
Computer Science (Springer-11645)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000133041
電子館藏
1圖書
電子書
EB QA402 M515 2016
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
http://dx.doi.org/10.1007/978-3-658-15728-9
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入