Name
Abstract | ||
|---|---|---|
AgentDiscover is a multi-agent based intelligent recommendation system, supporting real-time control and feedback, for building and execution workflows for knowledge discovery from databases (KDD). The aim of the proposed system is to deal with the complexity of KDD processes and to offer a tool that supports both researchers exploring KDD methods and non-expert users looking for quick results in this field. A prototype was developed in JADE and the approach was tested for a medical dataset. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/SYNASC.2007.57 | SYNASC |
Keywords | Field | DocType |
kdd method,knowledge discovery,non-expert user,execution workflows,quick result,medical dataset,kdd process,proposed system,real-time control,multi-agent system,intelligent recommendation system,database management systems,real time control,data mining,multi agent system,recommender system,multi agent systems | Recommender system,Intelligent decision support system,Computer science,Multi-agent system,Knowledge extraction,Workflow,Database | Conference |
ISBN | Citations | PageRank |
0-7695-3078-8 | 2 | 0.38 |
References | Authors | |
14 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Horia Emil Popa | 1 | 21 | 5.52 |
| Daniel Pop | 2 | 16 | 4.26 |
| Viorel Negru | 3 | 311 | 47.71 |
| Daniela Zaharie | 4 | 393 | 36.91 |