在空間關聯規則挖掘中，如何進行定量定性轉換是一個十分關鍵的問題，而云理論
正是一種處理該問題的有效工具。文章提出了一種基于云模型的屬性空間軟化分方法，并且通過研究傳統的關聯規則挖掘方法和空間數據本身的特點，對Apriori 算法進行了改進，提出了更適用于對空間數據進行挖掘的算法。最后通過實例測試，驗證了改進算法的有效性。
關鍵詞：云理論； 空間關聯規則； 空間數據挖掘； Apriori 算法

An Algorithm of Mining Spatial Association Rules based on Cloud Theory MENG Fan-rong ZHENG Zhong-pei CHEN Pei-pei (Computer Science and Technology Department, China University Of Mining And Technology,221008,China) Abstract: The transforms between qualitative concepts and their quantitative expressions plan an important role in spatial association mining，the cloud theory is this kind of powerful tools. In this paper, an attribute induction and concept promotion method on cloud model is proposed. By studying the methods of data mining and the? characters of spatial data，an improved spatial association rule mining algorithm based on Apriori is proposed. Finally an example is explained and confirmed this method validity.
Keywords: cloud theory; spatial association rules; spatial data mining; Apriori algorithm