TY  - BOOK
AU  - Celebi,M.Emre
AU  - Aydin,Kemal
ED  - SpringerLink (Online service)
TI  - Unsupervised Learning Algorithms
SN  - 9783319242118
AV  - TK1-9971 
U1  - 621.382 23
PY  - 2016///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Engineering
KW  - Computer communication systems
KW  - Data mining
KW  - Artificial intelligence
KW  - Pattern recognition
KW  - Computational intelligence
KW  - Electrical engineering
KW  - Communications Engineering, Networks
KW  - Computational Intelligence
KW  - Computer Communication Networks
KW  - Pattern Recognition
KW  - Artificial Intelligence (incl. Robotics)
KW  - Data Mining and Knowledge Discovery
N1  - Introduction -- Feature Construction -- Feature Extraction -- Feature Selection -- Association Rule Learning -- Clustering -- Anomaly/Novelty/Outlier Detection -- Evaluation of Unsupervised Learning -- Applications -- Conclusion
N2  - This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how withthe proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest include anomaly detection, clustering, feature extraction, and applications of unsupervised learning. Each chapter is contributed by a leading expert in the field
UR  - http://148.231.10.114:2048/login?url=http://dx.doi.org/10.1007/978-3-319-24211-8
ER  -