語系:
繁體中文
English
說明(常見問題)
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Machine learning techniques for onli...
~
SpringerLink (Online service)
Machine learning techniques for online social networks
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Machine learning techniques for online social networks/ edited by Tansel Ozyer, Reda Alhajj.
其他作者:
Ozyer, Tansel.
出版者:
Cham :Springer International Publishing : : 2018.,
面頁冊數:
viii, 236 p. :digital ; : 24 cm.;
Contained By:
Springer eBooks
標題:
Online social networks - Analysis. -
電子資源:
http://dx.doi.org/10.1007/978-3-319-89932-9
ISBN:
9783319899329
Machine learning techniques for online social networks
Machine learning techniques for online social networks
[electronic resource] /edited by Tansel Ozyer, Reda Alhajj. - Cham :Springer International Publishing :2018. - viii, 236 p. :digital ;24 cm. - Lecture notes in social networks,2190-5428. - Lecture notes in social networks..
Chapter1. Acceleration of Functional Cluster Extraction and Analysis of Cluster Affinity -- Chapter2. Delta-Hyperbolicity and the Core-Periphery Structure in Graphs -- Chapter3. A Framework for OSN Performance Evaluation Studies -- Chapter4. On The Problem of Multi-Staged Impression Allocation in Online Social Networks -- Chapter5. Order-of-Magnitude Popularity Estimation of Pirated Content -- Chapter6. Learning What to Share in Online Social Networks using Deep Reinforcement Learning -- Chapter7. Centrality and Community Scoring Functions in Incomplete Networks: Their Sensitivity, Robustness and Reliability -- Chapter8. Ameliorating Search Results Recommendation System based on K-means Clustering Algorithm and Distance Measurements -- Chapter9. Dynamics of large scale networks following a merger -- Chapter10. Cloud Assisted Personal Online Social Network -- Chapter11. Text-Based Analysis of Emotion by Considering Tweets.
The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies for analyzing social network data are covered. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis. Machine Learning Techniques for Online Social Networks will appeal to researchers and students in these fields.
ISBN: 9783319899329
Standard No.: 10.1007/978-3-319-89932-9doiSubjects--Topical Terms:
1205658
Online social networks
--Analysis.
LC Class. No.: HM742
Dewey Class. No.: 302.231
Machine learning techniques for online social networks
LDR
:02370nam a2200301 a 4500
001
926793
003
DE-He213
005
20181214143422.0
006
m d
007
cr nn 008maaau
008
190625s2018 gw s 0 eng d
020
$a
9783319899329
$q
(electronic bk.)
020
$a
9783319899312
$q
(paper)
024
7
$a
10.1007/978-3-319-89932-9
$2
doi
035
$a
978-3-319-89932-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
HM742
082
0 4
$a
302.231
$2
23
090
$a
HM742
$b
.M149 2018
245
0 0
$a
Machine learning techniques for online social networks
$h
[electronic resource] /
$c
edited by Tansel Ozyer, Reda Alhajj.
260
$a
Cham :
$c
2018.
$b
Springer International Publishing :
$b
Imprint: Springer,
300
$a
viii, 236 p. :
$b
digital ;
$c
24 cm.
490
1
$a
Lecture notes in social networks,
$x
2190-5428
505
0
$a
Chapter1. Acceleration of Functional Cluster Extraction and Analysis of Cluster Affinity -- Chapter2. Delta-Hyperbolicity and the Core-Periphery Structure in Graphs -- Chapter3. A Framework for OSN Performance Evaluation Studies -- Chapter4. On The Problem of Multi-Staged Impression Allocation in Online Social Networks -- Chapter5. Order-of-Magnitude Popularity Estimation of Pirated Content -- Chapter6. Learning What to Share in Online Social Networks using Deep Reinforcement Learning -- Chapter7. Centrality and Community Scoring Functions in Incomplete Networks: Their Sensitivity, Robustness and Reliability -- Chapter8. Ameliorating Search Results Recommendation System based on K-means Clustering Algorithm and Distance Measurements -- Chapter9. Dynamics of large scale networks following a merger -- Chapter10. Cloud Assisted Personal Online Social Network -- Chapter11. Text-Based Analysis of Emotion by Considering Tweets.
520
$a
The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies for analyzing social network data are covered. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis. Machine Learning Techniques for Online Social Networks will appeal to researchers and students in these fields.
650
0
$a
Online social networks
$x
Analysis.
$3
1205658
650
0
$a
Social media.
$3
780265
650
0
$a
Machine learning.
$3
561253
650
1 4
$a
Social Sciences.
$3
655031
650
2 4
$a
Computational Social Sciences.
$3
1141127
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
677765
650
2 4
$a
Social Media.
$3
1106917
650
2 4
$a
Artificial Intelligence (incl. Robotics)
$3
593924
700
1
$a
Ozyer, Tansel.
$3
888134
700
1
$a
Alhajj, Reda.
$3
1205657
710
2
$a
SpringerLink (Online service)
$3
593884
773
0
$t
Springer eBooks
830
0
$a
Lecture notes in social networks.
$3
1024533
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-89932-9
950
$a
Social Sciences (Springer-41176)
筆 0 讀者評論
多媒體
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼[密碼必須為2種組合(英文和數字)及長度為10碼以上]
登入