Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2012, Bristol, UK, September 24-28, 2012. Proceedings, Part I / 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 (SpringerNature-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 7523

Lecture Notes in Artificial Intelligence, 2945-9141 ; 7523

Language:

English

Subjects (All):

Data mining.

Artificial intelligence.

Pattern recognition systems.

Computer science-Mathematics.

Discrete mathematics.

Mathematical statistics.

Information storage and retrieval systems.

Data Mining and Knowledge Discovery.

Artificial Intelligence.

Automated 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.

Automated Pattern Recognition.

Discrete Mathematics in Computer Science.

Probability and Statistics in Computer Science.

Information Storage and Retrieval.

Physical Description:

1 online resource (XXVI, 879 pages) : 241 illustrations

Edition:

1st ed. 2012.

Contained In:

Springer Nature eBook

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:

Aassociation 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.

Other Format:

Printed edition:

ISBN:

978-3-642-33460-3

9783642334603

Access Restriction:

Restricted for use by site license.