关键词: 空间Co-Location模式, 模糊属性, 模糊Co-Location模式, 剪枝

Abstract: As one of the important research in spatial data mining, the spatial co-location pattern mining attracts more and more attention. In practical applications, in addition to the spatial information, the spatial features usually contain the attribute information which is important for the decision-making. However, the previous works stressed the spatial information only. Firstly, based on the fuzzification of attribute information, this paper defines the related concepts, including fuzzy feature, fuzzy co-location pattern, etc. Secondly, similar to the related concepts of traditional co-location mining, this paper defines some concepts of fuzzy co-location pattern, such as table instance and participation index, etc. Then, this paper proves the downward closure property of fuzzy co-location pattern, proposes a basic mining algorithm, and puts forward two pruning strategies so as to improve the mining performance. Finally, by extensive experiments, the efficiency and effectiveness of the algorithms are verified.

Key words: spatial co-location pattern, fuzzy attribute, fuzzy co-location pattern, pruning