Agents and Data Mining Interaction
10th International Workshop, ADMI 2014, Paris, France, May 5-9, 2014, Revised Selected Papers
Published on 25. June 2015
Book
Paperback/Softback
XI, 125 pages
978-3-319-20229-7 (ISBN)
Description
This book constitutes the thoroughly refereed and revised selected papers from the 10th International Workshop on Agents and Data Mining Interactions, ADMI 2014, held in Paris, France, in May 2014 as satellite workshop of AAMAS 2014, the 13th International Conference on Autonomous Agents and Multiagent Systems.The 11 papers presented were carefully reviewed and selected from numerous submissions for inclusion in this volume. They present current research and engineering results, as well as potential challenges and prospects encountered in the respective communities and the coupling between agents and data mining.
More details
Series
Edition
2015 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Research
Illustrations
54 s/w Abbildungen
XI, 125 p. 54 illus.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 8 mm
Weight
224 gr
ISBN-13
978-3-319-20229-7 (9783319202297)
DOI
10.1007/978-3-319-20230-3
Schweitzer Classification
Other editions
Additional editions
Longbing Cao | Yifeng Zeng | Bo An
Agents and Data Mining Interaction
10th International Workshop, ADMI 2014, Paris, France, May 5-9, 2014, Revised Selected Papers
E-Book
06/2015
Springer
€42.79
Available for download
Content
Learning Agents' Relations in Interactive Multiagent Dynamic Influence Diagrams.- Agent-Based Customer Profile Learning in 3G Recommender Systems: Ontology-Driven Multi-source Cross-Domain Case.- Modeling Temporal Propagation Dynamics in Multiplex Networks.- Mining Movement Patterns from Video Data to Inform Multi-agent Based Simulation.- Accessory-Based Multi-agent Simulating Platform on the Web.- Performance Evaluation of Agents and Multi-agent Systems Using Formal Specifications in Z Notation.- Reputation in Communities of Agent-Based Web Services Through Data Mining.- Data Mining Process Optimization in Computational Multi-agent Systems.- Diversifying the Storytelling Using Bayesian Networks.- A Coupled Similarity Kernel for Pairwise Support Vector Machine.