Please use this identifier to cite or link to this item:
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Title: | Machine Learning Techniques for Online Social Networks / |
Authors: | ezyer, Tansel. ; editor. ;;Alhajj, Reda. ; editor. ; |
subject: | Social sciences. ;;Social media. ;;Data Mining;Artificial Intelligence;Social Sciences. ;;Computational Social Sciences. ;;Data Mining and Knowledge Discovery;Social Media. ;;Artificial Intelligence and Robotics |
Year: | 2018 |
place: | Cham : |
Publisher: | Springer International Publishing : Imprint: Springer, |
Series/Report no.: | Lecture Notes in Social Networks, ; 2190-5428 ; Lecture Notes in Social Networks, ; 2190-5428 ; |
Abstract: | 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. . ; |
Description: | SpringerLink (Online service) ; HdE ; WaSeSS ; QA76 Hdig ; SFX ; Zdig ; WaSeSS ; Printed edition: ; Machine Learning Techniques for Online Social Networks ; 9783319899312 ; |
URI: | http://localhost/handle/Hannan/1767 |
ISBN: | 9783319899329 ; 9783319899312 (Print) ; |
More Information: | VIII, 236 p. 102 illus., 85 illus. in color. ; online resource. ; |
Appears in Collections: | مدیریت فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9783319899312.pdf | 10.12 MB | Adobe PDF | Preview File |
Title: | Machine Learning Techniques for Online Social Networks / |
Authors: | ezyer, Tansel. ; editor. ;;Alhajj, Reda. ; editor. ; |
subject: | Social sciences. ;;Social media. ;;Data Mining;Artificial Intelligence;Social Sciences. ;;Computational Social Sciences. ;;Data Mining and Knowledge Discovery;Social Media. ;;Artificial Intelligence and Robotics |
Year: | 2018 |
place: | Cham : |
Publisher: | Springer International Publishing : Imprint: Springer, |
Series/Report no.: | Lecture Notes in Social Networks, ; 2190-5428 ; Lecture Notes in Social Networks, ; 2190-5428 ; |
Abstract: | 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. . ; |
Description: | SpringerLink (Online service) ; HdE ; WaSeSS ; QA76 Hdig ; SFX ; Zdig ; WaSeSS ; Printed edition: ; Machine Learning Techniques for Online Social Networks ; 9783319899312 ; |
URI: | http://localhost/handle/Hannan/1767 |
ISBN: | 9783319899329 ; 9783319899312 (Print) ; |
More Information: | VIII, 236 p. 102 illus., 85 illus. in color. ; online resource. ; |
Appears in Collections: | مدیریت فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9783319899312.pdf | 10.12 MB | Adobe PDF | Preview File |
Title: | Machine Learning Techniques for Online Social Networks / |
Authors: | ezyer, Tansel. ; editor. ;;Alhajj, Reda. ; editor. ; |
subject: | Social sciences. ;;Social media. ;;Data Mining;Artificial Intelligence;Social Sciences. ;;Computational Social Sciences. ;;Data Mining and Knowledge Discovery;Social Media. ;;Artificial Intelligence and Robotics |
Year: | 2018 |
place: | Cham : |
Publisher: | Springer International Publishing : Imprint: Springer, |
Series/Report no.: | Lecture Notes in Social Networks, ; 2190-5428 ; Lecture Notes in Social Networks, ; 2190-5428 ; |
Abstract: | 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. . ; |
Description: | SpringerLink (Online service) ; HdE ; WaSeSS ; QA76 Hdig ; SFX ; Zdig ; WaSeSS ; Printed edition: ; Machine Learning Techniques for Online Social Networks ; 9783319899312 ; |
URI: | http://localhost/handle/Hannan/1767 |
ISBN: | 9783319899329 ; 9783319899312 (Print) ; |
More Information: | VIII, 236 p. 102 illus., 85 illus. in color. ; online resource. ; |
Appears in Collections: | مدیریت فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9783319899312.pdf | 10.12 MB | Adobe PDF | Preview File |