TY  - BOOK
AU  - Flach,Peter A.
AU  - Bie,Tijl
AU  - Cristianini,Nello
ED  - SpringerLink (Online service)
TI  - Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II 
T2  - Lecture Notes in Computer Science,
SN  - 9783642334863
AV  - QA76.9.D343 
U1  - 006.312 23
PY  - 2012///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Computer science
KW  - Computational complexity
KW  - Data mining
KW  - Information storage and retrieval systems
KW  - Artificial intelligence
KW  - Optical pattern recognition
KW  - Computer Science
KW  - Data Mining and Knowledge Discovery
KW  - Artificial Intelligence (incl. Robotics)
KW  - Pattern Recognition
KW  - Discrete Mathematics in Computer Science
KW  - Probability and Statistics in Computer Science
KW  - Information Storage and Retrieval
N1  - Privacy and security -- rankings and recommendations -- reinforcement learning and planning -- rule mining and subgroup discovery -- semi-supervised and transductive learning -- sensor data -- sequence and string mining -- social network mining -- spatial and geographical data mining -- statistical methods and evaluation -- time series and temporal data mining -- transfer learning
N2  - This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012. The 105 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 443 submissions. The final sections of the proceedings are devoted to Demo and Nectar papers. The Demo track includes 10 papers (from 19 submissions) and the Nectar track includes 4 papers (from 14 submissions). The papers grouped in topical sections on association rules and frequent patterns; Bayesian learning and graphical models; classification; dimensionality reduction, feature selection and extraction; distance-based methods and kernels; ensemble methods; graph and tree mining; large-scale, distributed and parallel mining and learning; multi-relational mining and learning; multi-task learning; natural language processing; online learning and data streams; privacy and security; rankings and recommendations; reinforcement learning and planning; rule mining and subgroup discovery; semi-supervised and transductive learning; sensor data; sequence and string mining; social network mining; spatial and geographical data mining; statistical methods and evaluation; time series and temporal data mining; and transfer learning
UR  - http://dx.doi.org/10.1007/978-3-642-33486-3
ER  -