Name
Abstract | ||
|---|---|---|
jCOLIBRI is currently a reference platform in the CBR community for building CBR systems that includes facilities to design different types of CBR applications \cite{ICCBR05CBRT,jscp07BuildingCBRsystems,AI06OntBasedCBR}. In this paper we focus in some recently included tools that allow the improvement of performance of previously designed applications. These optimization tools mainly facilitate to adjust features on large case bases like clustering and noise reduction techniques, and to adjust processes like refine similarity metrics through case base visualization, parallelization of retrieval or distribution of the case base and reasoning thought different agents. We present the tools and exemplify how to use them in a real scenario. We have developed an experiment for the automatic classification of a textual case base made of 1500 academic journals belonging to 20 different areas. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICTAI.2009.130 | ICTAI |
Keywords | Field | DocType |
case base visualization,cbr system,cbr application,case base,different agent,textual case base,cbr applications,large case base,different type,cbr community,different area,accuracy,noise reduction,data mining,optimization,case base reasoning,noise measurement,clustering,artificial intelligence,cognition,case based reasoning | Noise reduction,Data mining,Noise measurement,Computer science,Visualization,Case base,Software,Artificial intelligence,Boosting (machine learning),Case-based reasoning,Cluster analysis,Machine learning | Conference |
ISSN | ISBN | Citations |
1082-3409 | 978-0-7695-3920-1 | 1 |
PageRank | References | Authors |
0.36 | 9 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan A. Recio-garcía | 1 | 185 | 14.75 |
| Belén Díaz-agudo | 2 | 484 | 49.71 |
| Pedro A. González-Calero | 3 | 488 | 55.63 |
| Recio-Garcia, J.A. | 4 | 8 | 1.13 |
| Diaz-Agudo, B. | 5 | 1 | 0.36 |
| Gonzalez-Calero, P.A. | 6 | 1 | 0.36 |