Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part II / edited by Peter A. Flach, Tijl De Bie, Nello Cristianini.

Format:

Book

Contributor:

Flach, Peter A., editor.

De Bie, Tijl, editor.

Cristianini, Nello, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 7524.

Lecture Notes in Artificial Intelligence ; 7524

Language:

English

Subjects (All):

Data mining.

Artificial intelligence.

Pattern perception.

Computer science--Mathematics.

Computer science.

Mathematical statistics.

Information storage and retrieval.

Data Mining and Knowledge Discovery.

Artificial Intelligence.

Pattern Recognition.

Discrete Mathematics in Computer Science.

Probability and Statistics in Computer Science.

Information Storage and Retrieval.

Local Subjects:

Data Mining and Knowledge Discovery.

Artificial Intelligence.

Pattern Recognition.

Discrete Mathematics in Computer Science.

Probability and Statistics in Computer Science.

Information Storage and Retrieval.

Physical Description:

1 online resource (XXVI, 867 pages) : 245 illustrations.

Edition:

First edition 2012.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.

System Details:

text file PDF

Summary:

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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-642-33486-3

9783642334863

Access Restriction:

Restricted for use by site license.