語系:
繁體中文
English
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
Social network based big data analys...
~
Kaya, Mehmet.
FindBook
Google Book
Amazon
博客來
Social network based big data analysis and applications
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Social network based big data analysis and applications/ edited by Mehmet Kaya ... [et al.].
其他作者:
Kaya, Mehmet.
出版者:
Cham :Springer International Publishing : : 2018.,
面頁冊數:
x, 249 p. :ill., digital ;24 cm.
內容註:
Chapter1. Twitter as a Source for Time and Domain Dependent Sentiment Lexicons -- Chapter2. Hiding in Plain Sight: The Anatomy of Malicious Pages on Facebook -- Chapter3. Extraction and Analysis of Dynamic Conversational Networks from TV Series -- Chapter4. Diversity and Influence as Key Measures to Assess Candidates for Hiring or Promotion in Academia -- Chapter5. Timelines of Prostate Cancer Biomarkers -- Chapter6. Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks -- Chapter7. Influence and Extension of the Spiral of Silence in Social Networks: A Data-driven Approach -- Chapter8. Prepaid or Postpaid? That is the question.\\ Novel Methods of Subscription Type Prediction in Mobile Phone Services -- Chapter9. Dynamic Pattern Detection for Big Data Stream Analytics -- Chapter10. Community-based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation -- Chapter11. Combining Feature Extraction and Clustering for Better Face Recognition.
Contained By:
Springer eBooks
標題:
Online social networks. -
電子資源:
http://dx.doi.org/10.1007/978-3-319-78196-9
ISBN:
9783319781969
Social network based big data analysis and applications
Social network based big data analysis and applications
[electronic resource] /edited by Mehmet Kaya ... [et al.]. - Cham :Springer International Publishing :2018. - x, 249 p. :ill., digital ;24 cm. - Lecture notes in social networks,2190-5428. - Lecture notes in social networks..
Chapter1. Twitter as a Source for Time and Domain Dependent Sentiment Lexicons -- Chapter2. Hiding in Plain Sight: The Anatomy of Malicious Pages on Facebook -- Chapter3. Extraction and Analysis of Dynamic Conversational Networks from TV Series -- Chapter4. Diversity and Influence as Key Measures to Assess Candidates for Hiring or Promotion in Academia -- Chapter5. Timelines of Prostate Cancer Biomarkers -- Chapter6. Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks -- Chapter7. Influence and Extension of the Spiral of Silence in Social Networks: A Data-driven Approach -- Chapter8. Prepaid or Postpaid? That is the question.\\ Novel Methods of Subscription Type Prediction in Mobile Phone Services -- Chapter9. Dynamic Pattern Detection for Big Data Stream Analytics -- Chapter10. Community-based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation -- Chapter11. Combining Feature Extraction and Clustering for Better Face Recognition.
This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.
ISBN: 9783319781969
Standard No.: 10.1007/978-3-319-78196-9doiSubjects--Topical Terms:
624374
Online social networks.
LC Class. No.: HM742 / .S635 2018
Dewey Class. No.: 302.30285
Social network based big data analysis and applications
LDR
:02765nmm a2200301 a 4500
001
2146434
003
DE-He213
005
20181212101838.0
006
m d
007
cr nn 008maaau
008
190227s2018 gw s 0 eng d
020
$a
9783319781969
$q
(electronic bk.)
020
$a
9783319781952
$q
(paper)
024
7
$a
10.1007/978-3-319-78196-9
$2
doi
035
$a
978-3-319-78196-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
HM742
$b
.S635 2018
082
0 4
$a
302.30285
$2
23
090
$a
HM742
$b
.S678 2018
245
0 0
$a
Social network based big data analysis and applications
$h
[electronic resource] /
$c
edited by Mehmet Kaya ... [et al.].
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2018.
300
$a
x, 249 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Lecture notes in social networks,
$x
2190-5428
505
0
$a
Chapter1. Twitter as a Source for Time and Domain Dependent Sentiment Lexicons -- Chapter2. Hiding in Plain Sight: The Anatomy of Malicious Pages on Facebook -- Chapter3. Extraction and Analysis of Dynamic Conversational Networks from TV Series -- Chapter4. Diversity and Influence as Key Measures to Assess Candidates for Hiring or Promotion in Academia -- Chapter5. Timelines of Prostate Cancer Biomarkers -- Chapter6. Exploring the Role of Intrinsic Nodal Activation on the Spread of Influence in Complex Networks -- Chapter7. Influence and Extension of the Spiral of Silence in Social Networks: A Data-driven Approach -- Chapter8. Prepaid or Postpaid? That is the question.\\ Novel Methods of Subscription Type Prediction in Mobile Phone Services -- Chapter9. Dynamic Pattern Detection for Big Data Stream Analytics -- Chapter10. Community-based Recommendation for Cold-Start Problem: A Case Study of Reciprocal Online Dating Recommendation -- Chapter11. Combining Feature Extraction and Clustering for Better Face Recognition.
520
$a
This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.
650
0
$a
Online social networks.
$3
624374
650
0
$a
Big data.
$3
2045508
650
1 4
$a
Social Sciences.
$3
786955
650
2 4
$a
Computational Social Sciences.
$3
3220598
650
2 4
$a
Big Data.
$3
3134868
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
898250
650
2 4
$a
Applications of Graph Theory and Complex Networks.
$3
3134760
700
1
$a
Kaya, Mehmet.
$3
3226537
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer eBooks
830
0
$a
Lecture notes in social networks.
$3
2058983
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-78196-9
950
$a
Social Sciences (Springer-41176)
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
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
W9347950
電子資源
11.線上閱覽_V
電子書
EB HM742 .S635 2018
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入