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
Practical graph analytics with Apach...
~
Logothetis, Dionysios.
Practical graph analytics with Apache Giraph
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Practical graph analytics with Apache Giraphby Claudio Martella, Roman Shaposhnik, Dionysios Logothetis.
作者:
Martella, Claudio.
其他作者:
Shaposhnik, Roman.
出版者:
Berkeley, CA :Apress :2015.
面頁冊數:
xix, 315 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
標題:
Graph theoryData processing.
電子資源:
http://dx.doi.org/10.1007/978-1-4842-1251-6
ISBN:
9781484212516$q(electronic bk.)
Practical graph analytics with Apache Giraph
Martella, Claudio.
Practical graph analytics with Apache Giraph
[electronic resource] /by Claudio Martella, Roman Shaposhnik, Dionysios Logothetis. - Berkeley, CA :Apress :2015. - xix, 315 p. :ill., digital ;24 cm.
Practical Graph Analytics with Apache Giraph helps you build data mining and machine learning applications using the Apache Foundation's Giraph framework for graph processing. This is the same framework as used by Facebook, Google, and other social media analytics operations to derive business value from vast amounts of interconnected data points. Graphs arise in a wealth of data scenarios and describe the connections that are naturally formed in both digital and real worlds. Examples of such connections abound in online social networks such as Facebook and Twitter, among users who rate movies from services like Netflix and Amazon Prime, and are useful even in the context of biological networks for scientific research. Whether in the context of business or science, viewing data as connected adds value by increasing the amount of information available to be drawn from that data and put to use in generating new revenue or scientific opportunities. Apache Giraph offers a simple yet flexible programming model targeted to graph algorithms and designed to scale easily to accommodate massive amounts of data. Originally developed at Yahoo!, Giraph is now a top top-level project at the Apache Foundation, and it enlists contributors from companies such as Facebook, LinkedIn, and Twitter. Practical Graph Analytics with Apache Giraph brings the power of Apache Giraph to you, showing how to harness the power of graph processing for your own data by building sophisticated graph analytics applications using the very same framework that is relied upon by some of the largest players in the industry today.
ISBN: 9781484212516$q(electronic bk.)
Standard No.: 10.1007/978-1-4842-1251-6doiSubjects--Topical Terms:
296758
Graph theory
--Data processing.
LC Class. No.: QA166
Dewey Class. No.: 511.5
Practical graph analytics with Apache Giraph
LDR
:02575nmm a2200301 a 4500
001
477144
003
DE-He213
005
20160331163533.0
006
m d
007
cr nn 008maaau
008
160526s2015 cau s 0 eng d
020
$a
9781484212516$q(electronic bk.)
020
$a
9781484212523$q(paper)
024
7
$a
10.1007/978-1-4842-1251-6
$2
doi
035
$a
978-1-4842-1251-6
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA166
072
7
$a
UY
$2
bicssc
072
7
$a
COM014000
$2
bisacsh
082
0 4
$a
511.5
$2
23
090
$a
QA166
$b
.M376 2015
100
1
$a
Martella, Claudio.
$3
732041
245
1 0
$a
Practical graph analytics with Apache Giraph
$h
[electronic resource] /
$c
by Claudio Martella, Roman Shaposhnik, Dionysios Logothetis.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2015.
300
$a
xix, 315 p. :
$b
ill., digital ;
$c
24 cm.
520
$a
Practical Graph Analytics with Apache Giraph helps you build data mining and machine learning applications using the Apache Foundation's Giraph framework for graph processing. This is the same framework as used by Facebook, Google, and other social media analytics operations to derive business value from vast amounts of interconnected data points. Graphs arise in a wealth of data scenarios and describe the connections that are naturally formed in both digital and real worlds. Examples of such connections abound in online social networks such as Facebook and Twitter, among users who rate movies from services like Netflix and Amazon Prime, and are useful even in the context of biological networks for scientific research. Whether in the context of business or science, viewing data as connected adds value by increasing the amount of information available to be drawn from that data and put to use in generating new revenue or scientific opportunities. Apache Giraph offers a simple yet flexible programming model targeted to graph algorithms and designed to scale easily to accommodate massive amounts of data. Originally developed at Yahoo!, Giraph is now a top top-level project at the Apache Foundation, and it enlists contributors from companies such as Facebook, LinkedIn, and Twitter. Practical Graph Analytics with Apache Giraph brings the power of Apache Giraph to you, showing how to harness the power of graph processing for your own data by building sophisticated graph analytics applications using the very same framework that is relied upon by some of the largest players in the industry today.
650
0
$a
Graph theory
$x
Data processing.
$3
296758
650
0
$a
Big data.
$3
609582
650
1 4
$a
Computer Science.
$3
212513
650
2 4
$a
Computer Science, general.
$3
274540
650
2 4
$a
Computational Biology/Bioinformatics.
$3
274833
700
1
$a
Shaposhnik, Roman.
$3
732042
700
1
$a
Logothetis, Dionysios.
$3
732043
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-1-4842-1251-6
950
$a
Professional and Applied Computing (Springer-12059)
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
000000120364
電子館藏
1圖書
電子書
EB QA166 M376 2015
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/10.1007/978-1-4842-1251-6
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