A Bi-Clustering Agent-based Approach for Map Segmentation

This source preferred by Hamid Bouchachia

This data was imported from DBLP:

Authors: Bouchachia, A. and Prossegger, M.

http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4911322

Journal: IEEE IA

Pages: 99-105

Publisher: IEEE

ISBN: 978-1-4244-2767-3

This data was imported from Scopus:

Authors: Bouchachia, A. and Prossegger, M.

Journal: 2009 IEEE Symposium on Intelligent Agents, IA 2009 - Proceedings

Pages: 99-105

ISBN: 9781424427673

DOI: 10.1109/IA.2009.4927506

The present paper introduces an agent-based ap-proach for clustering geographical data. In this approach,a multi-agent architecture is proposed. It consists of three competence levels: specialized gatherers (G-Agents), breakers(B-Agents), mappers (M-Agents). Each of these agents have particular role in the process of segmentation. Using bi-clustering, the approach combines the different views of the data (according to the land-use classes) to obtain a useful segmentation which serves as an instrument of decision making. Illustrative simulation of the multi-agent architecture on real-world data is reported. ©2009 IEEE.

This data was imported from Web of Science (Lite):

Authors: Bouchachia, A., Prossegger, M. and IEEE

Journal: IA 2009: IEEE SYMPOSIUM ON INTELLIGENT AGENTS

Pages: 99-+

ISBN: 978-1-4244-2767-3

The data on this page was last updated at 04:48 on May 21, 2018.