模糊資料庫關聯表之不失真切割

Lossless Decomposition of Fuzzy Relations on Fuzzy Databases

李大仰(Ta-Yang Lee)

指導教授 ： 劉俞志

元智大學/資訊學院/資訊管理學系/碩士(2004年)

摘要

資料庫關聯表的正規化可用以避免資料重覆和更新異常，正規化強調不失真的切割表格，而切割的結果取決於值組的重覆性定義。在延伸可能性模糊資料模式中，值組間的相似度超過門檻值就被視為重覆值組，但因為值組間的相似度所構成之關係不具遞移性，所以無法根據相似度將值組分成數個不交集的群集，並合併同一群集中的值組。而在相似型模糊資料模式中，值組間相似度所構成的關係具有遞移性，故合併時不會發生前者的問題。本研究即探討利用現有的值組相似度計算方法及模糊功能相依之定義，找出在延伸可能性和相似型模糊資料下之關聯表的不失真切割。

關鍵字

不失真切割 ； 模糊關聯資料庫

並列摘要

Normalization of relations on relational databases can avoid the redundancies of data and update anomalies, and it emphasizes the lossless decomposition of relations. The outcome of decomposition depends on the definition of the redundancies of tuples. In Extended Possibility-Based fuzzy data model, if the resemblance between the tuples exceeds the threshold, we can say that they are redundant tuples, but the relation of the resemblance doesn’t have the transitivity, so that there is no way to divide the tuples into non overlapping groups, and to merge the tuples in the same group. But, in the Similarity-Based fuzzy data model, the resemblance relation of redundant tuples has transitivity, and when merging the tuples, there is no previous problem. This study just discussed how to use of the definitions of calculating the resemblance between tuples and the definitions of fuzzy functional dependencies up to now, and then find out a way to lossless decompose the relations in Extended- Possibility and Similarity-Based fuzzy data model.

並列關鍵字

lossless decomposition ； fuzzy relational databases

參考文獻

[2]. G.Q. Chen, J. Vandenbulcke and E.E. Kerre, A General Treatment of Data Redundancy in a Fuzzy Relational Data Model, Journal of American Society of Information Science,Vol. 43, pp.304-311, 1992

[3]. G.Q. Chen, J. Vandenbulcke and E.E. Kerre, On the lossless-join decomposition of relation scheme(s) in a fuzzy relational data model, Second International Symposium on Uncertainty Modeling and Analysis, Proceedings ISUMA '93 , pp.440 — 446,1993.

[4]. G.Q. Chen, E.E. Kerre, and J. Vandenbulcke, Normalization Based on Fuzzy Functional Dependency in a Fuzzy Relational Data Model, Information Systems, Vol. 21, pp.299-310, 1996.

[5]. H. Prade and C. Testamale, Generalizing Database Relational Algebra for the Treatment of Incomplete or Uncertain Information and Vague Queries, Information Sciences, Vol. 34, pp.115-143, 1984

[6]. J.C Cubero and M.A Vila, A New Definition of Fuzzy Functional Dependency in Fuzzy Relational Databases, International Journal on Intelligent Systems, Vol.9, pp. 441-448, 1994.