The Z notation: a reference manual
The Z notation: a reference manual
ACM Computing Surveys (CSUR)
Classification by pairwise coupling
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Improvements to Platt's SMO Algorithm for SVM Classifier Design
Neural Computation
Developing Multi-Agent Systems with JADE (Wiley Series in Agent Technology)
Developing Multi-Agent Systems with JADE (Wiley Series in Agent Technology)
Agent-mining interaction: an emerging area
AIS-ADM'07 Proceedings of the 2nd international conference on Autonomous intelligent systems: agents and data mining
Agent services-driven plug-and-play in F-TRADE
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
| Hi-index | 0.00 |
Data mining researches focus on algorithms that mine valuable patterns from particular domain. Apart from the theoretical research, experiments take a vast amount of effort to build. In this paper, we propose an integrated framework that utilises a multi-agent system to support the researchers to rapidly develop experiments. Moreover, the proposed framework allows extension and integration for future researches in mutual aspects of agent and data mining. The paper describes the details of the framework and also presents a sample implementation.