Abstract
Database integration is much more complex in the context of fuzzy databases than in classical databases due to the measurement of the closeness of attribute values. In extended possibility-based fuzzy relational databases, the measurement comprises parameters in addition to attribute values. As the parameters used in databases are different, the closeness of the same pairs of attribute values will not be the same. It leads into the problem in defining the data redundancy consistently after data integration. However, the requirement of employing identical parameters in different databases is too stern to follow. This paper studies the closeness of attribute values varying from parameters of the measurement, and provides a flexible guide to define the parameters in fuzzy databases to be integrated.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the International Conference on Artificial Intelligence IC-AI 2003 |
| Editors | H.R. Arabnia, R. Joshua, Y. Mun, H.R. Arabnia, R. Joshua, Y. Mun |
| Pages | 988-993 |
| Number of pages | 6 |
| Volume | 2 |
| Publication status | Published - 2003 |
| Externally published | Yes |
| Event | Proceedings of the International Conference on Artificial Intelligence, IC-AI 2003 - Las Vegas, NV, United States Duration: Jun 23 2003 → Jun 26 2003 |
Other
| Other | Proceedings of the International Conference on Artificial Intelligence, IC-AI 2003 |
|---|---|
| Country/Territory | United States |
| City | Las Vegas, NV |
| Period | 6/23/03 → 6/26/03 |
Keywords
- Data integration
- Fuzzy databases
- Proximity relations
ASJC Scopus subject areas
- Artificial Intelligence