Examining concepts that change over time has been an active area of research within data mining. This paper presents a new method that functions in contexts where concept drift is present, while also allowing for modification of the instances themselves as they change over time. This method is well suited to domains where subjects of interest are sampled multiple times, and where they may migrate from one resultant concept to another. The method presented here is an extensive modification to the conceptual clustering algorithm COBWEB, and is titled DynamicWEB.
History
Publication title
AI 2008: Advances in Artificial Intelligence 21st Australasian Joint Conference on Artificial Intelligence
Volume
Lecture Notes in Computer Science 5360
Editors
Wobcke, W & Zhang, M
Pagination
454-460
ISBN
3-540-89377-6
Department/School
School of Information and Communication Technology
Publisher
Springer-Verlag
Place of publication
Berlin, Germany
Event title
AJCAI
Event Venue
Auckland, New Zealand
Date of Event (Start Date)
2008-12-01
Date of Event (End Date)
2008-12-05
Rights statement
Copyright 2008 Springer Berlin Heidelberg
Repository Status
Restricted
Socio-economic Objectives
Information systems, technologies and services not elsewhere classified