Name
Abstract | ||
|---|---|---|
One key aspect of exploiting the huge amount of autonomous and heterogeneous data sources in the Internet is not only how to retrieve, collect and integrate relevant information but to discover previously unknown, implicit and valuable knowledge. In recent years several approaches to distributed data mining and knowledge discovery have been developed, but only a few of them make use of intelligent agents. This paper is intended to argue for the potential added value of using agent technology in the domain of knowledge discovery. We briefly review and classify existing approaches to agent-based distributed data mining, propose a novel approach to distributed data clustering based on density estimation, and discuss issues of its agent-oriented implementation. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/3-540-36561-3_5 | AgentLink |
Keywords | Field | DocType |
data mining,intelligent agent,knowledge discovery,density estimation,agent-oriented implementation,huge amount,heterogeneous data source,agent technology,kdec scheme,key aspect,valuable knowledge | Data science,Data mining,Data stream mining,Intelligent agent,Computer science,Mobile agent,Added value,Information extraction,Knowledge extraction,Cluster analysis,The Internet | Conference |
Volume | ISSN | ISBN |
2586 | 0302-9743 | 3-540-00759-8 |
Citations | PageRank | References |
51 | 3.10 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthias Klusch | 1 | 2591 | 271.67 |
| Stefano Lodi | 2 | 231 | 21.96 |
| G. Moro | 3 | 192 | 16.25 |