國立高雄大學圖資館 |

Language: English

Back

From Social Data Mining and Analysis...

Erdogan, Ozcan.

From Social Data Mining and Analysis to Prediction and Community Detection

Record Type:	Electronic resources : Monograph/item
Title/Author:	From Social Data Mining and Analysis to Prediction and Community Detectionedited by Mehmet Kaya, Ozcan Erdogan, Jon Rokne.
other author:	Kaya, Mehmet.
Published:	Cham :Springer International Publishing :2017.
Description:	x, 245 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Data mining.
Online resource:	http://dx.doi.org/10.1007/978-3-319-51367-6
ISBN:	9783319513676$q(electronic bk.)

From Social Data Mining and Analysis to Prediction and Community Detection
From Social Data Mining and Analysis to Prediction and Community Detection[electronic resource] /edited by Mehmet Kaya, Ozcan Erdogan, Jon Rokne. - Cham :Springer International Publishing :2017. - x, 245 p. :ill., digital ;24 cm. - Lecture notes in social networks,2190-5428. - Lecture notes in social networks..

Chapter1. An Offline-Online Visual Framework for Clustering Memes in Social Media -- Chapter2. A System for Email Recipient Prediction -- Chapter3. A Credibility Assessment Model for Online Social Network Content -- Chapter4. Web Search Engine based Representation for Arabic Tweets Categorization -- Chapter5. Sentiment Trends and Classifying Stocks using P-Trees -- Chapter6. Mining Community Structure with Node Embeddings -- Chapter7. A LexDFS-based Approach on finding compact communities -- Chapter8. Computational Data Sciences and Regulation of Banking and Financial Services -- Chapter9. Frequent and Non-Frequent Sequential Itemsets Detection.

This book presents the state-of-the-art in various aspects of analysis and mining of online social networks. Within the broader context of online social networks, it focuses on important and upcoming topics of social network analysis and mining. The book collects chapters that are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2015), which was held in Paris, France in August 2015. All papers have been peer reviewed and checked carefully for overlap with the literature. The book will appeal to students and researchers in social network analysis/mining and machine learning.

ISBN: 9783319513676$q(electronic bk.)

Standard No.: 10.1007/978-3-319-51367-6doiSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

From Social Data Mining and Analysis to Prediction and Community Detection
LDR:02402nmm a2200337 a 4500 001 508876
003 DE-He213
005 20170321120910.0
006 m d
007 cr nn 008maaau
008 171121s2017 gw s 0 eng d
020 $a 9783319513676$q(electronic bk.)
020 $a 9783319513669$q(paper)
024 7 $a 10.1007/978-3-319-51367-6 $2 doi
035 $a 978-3-319-51367-6
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343
072 7 $a UNF $2 bicssc
072 7 $a UYQE $2 bicssc
072 7 $a COM021030 $2 bisacsh
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b F931 2017
245 0 0 $a From Social Data Mining and Analysis to Prediction and Community Detection $h [electronic resource] / $c edited by Mehmet Kaya, Ozcan Erdogan, Jon Rokne.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a x, 245 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in social networks, $x 2190-5428
505 0 $a Chapter1. An Offline-Online Visual Framework for Clustering Memes in Social Media -- Chapter2. A System for Email Recipient Prediction -- Chapter3. A Credibility Assessment Model for Online Social Network Content -- Chapter4. Web Search Engine based Representation for Arabic Tweets Categorization -- Chapter5. Sentiment Trends and Classifying Stocks using P-Trees -- Chapter6. Mining Community Structure with Node Embeddings -- Chapter7. A LexDFS-based Approach on finding compact communities -- Chapter8. Computational Data Sciences and Regulation of Banking and Financial Services -- Chapter9. Frequent and Non-Frequent Sequential Itemsets Detection.
520 $a This book presents the state-of-the-art in various aspects of analysis and mining of online social networks. Within the broader context of online social networks, it focuses on important and upcoming topics of social network analysis and mining. The book collects chapters that are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM'2015), which was held in Paris, France in August 2015. All papers have been peer reviewed and checked carefully for overlap with the literature. The book will appeal to students and researchers in social network analysis/mining and machine learning.
650 0 $a Data mining. $3 184440
650 1 4 $a Computer Science. $3 212513
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
650 2 4 $a Applications of Graph Theory and Complex Networks. $3 759901
700 1 $a Kaya, Mehmet. $3 775307
700 1 $a Erdogan, Ozcan. $3 775308
700 1 $a Rokne, Jon. $3 701612
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Lecture notes in social networks. $3 679300
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-51367-6
950 $a Computer Science (Springer-11645)