实例位置模糊的空间co-location模式挖掘研究

实例位置模糊在许多领域里都有着非常重要的应用,比如生物医学图像数据库和地理信息系统(geographic information system,GIS)。研究了实例位置模糊的空间co-location模式挖掘问题。定义了实例位置模糊的空间co-location模式挖掘的相关概念,包括实例位置模糊、位置参与率等;给出了基本算法来挖掘实例位置模糊的co-location模式;提出了两种改进算法,即基于网格的距离计算和减枝候选模式,以提高挖掘性能,加快co-location规则的产生。通过大量的实验,说明了基本算法及其改进算法的效果和效率。

Mining Spatial Co-location Patterns for Fuzzy Location of Instances

Fuzzy location of instances can be applied to many areas, such as biomedical image databases, geographic information system (GIS) and more. This paper investigates the spatial co-location patterns mining problem for fuzzy location of instances. Firstly, it defines the related concepts of co-location patterns mining for fuzzy location of instances, including fuzzy location of instances, location participation ratio, etc. Secondly, it proposes a basic algorithm to mine co-location patterns from fuzzy location of instances. Then, it puts forward two kinds of the improved algorithms, grid-based distance calculation and the pruning candidate patterns, so as to improve the mining performance and accelerate the co-location rule generation. Finally, by extensive experiments, this paper verifies the efficiency and effectiveness of the algorithms.