Name
Abstract | ||
|---|---|---|
Time plays a key role in describing stories and cases. In the last decades, great efforts have been done to develop Case-Based Reasoning (CBR) systems that can cope with the temporal dimension. Despite this kind of system finds it difficult to maintain their case-base, little attention has been paid to maintain temporal case-bases. Case-Base Maintenance (CBM) algorithms are useful tools to build efficient and reliable CBR systems. In this work, we propose the extension of different CBM approaches to deal with this problem. Five temporal CBM algorithms are proposed (t-CNN, t-RENN, t-DROP1, t-ICF and t-RC-FP). These algorithms make the maintenance of case-bases possible when cases are temporal event sequences. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-11209-1_19 | ICCBR |
Keywords | Field | DocType |
Case-Base Maintenance,Temporal CBR framework,Algorithms | Data mining,Computer science,Algorithm,Case base,Artificial intelligence,Machine learning | Conference |
Citations | PageRank | References |
2 | 0.36 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eduardo Lupiani | 1 | 20 | 3.63 |
| José M. Juarez | 2 | 165 | 19.28 |
| José Palma | 3 | 120 | 14.28 |