Compatible parameters for semantic measurement in extended fuzzy relational databases

Julie Yu Chih Liu, Tsu Hao Chang

研究成果: 書貢獻/報告類型會議貢獻

摘要

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.

原文英語
主出版物標題Proceedings of the International Conference on Artificial Intelligence IC-AI 2003
編輯H.R. Arabnia, R. Joshua, Y. Mun, H.R. Arabnia, R. Joshua, Y. Mun
頁面988-993
頁數6
2
出版狀態已發佈 - 2003
對外發佈
事件Proceedings of the International Conference on Artificial Intelligence, IC-AI 2003 - Las Vegas, NV, 美国
持續時間: 六月 23 2003六月 26 2003

其他

其他Proceedings of the International Conference on Artificial Intelligence, IC-AI 2003
國家/地區美国
城市Las Vegas, NV
期間6/23/036/26/03

ASJC Scopus subject areas

  • 人工智慧

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