TY  - GEN
N2  - 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.
DO  - 10.1007/978-3-319-89932-9
DO  - doi
AB  - 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.
T1  - Machine learning techniques for online social networks /
DA  - [2018]
CY  - Cham, Switzerland :
AU  - Özyer, Tansel,
AU  - Alhajj, Reda,
CN  - HM742
PB  - Springer,
PP  - Cham, Switzerland :
PY  - [2018]
ID  - 839634
KW  - Online social networks
KW  - Social media.
KW  - Machine learning.
SN  - 9783319899329
SN  - 3319899325
TI  - Machine learning techniques for online social networks /
LK  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-89932-9
UR  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-89932-9
ER  -