对空间数据不断深入的应用需求，推动了空间co-location模式挖掘技术的研究与发展。正如随机性的存在不可避免一样，模糊性的存在在许多场合也是一个不可回避的事实。比如度量用户感兴趣的模式往往具有不同程度的模糊性。因此，本项目拟系统研究空间co-location模式挖掘中的模糊技术，具体包括基于模糊集论的空间co-location模式的有趣性度量理论和挖掘方法、交互式空间co-location模式挖掘的模糊集论方法以及面向海量空间数据的co-location模式的模糊挖掘算法。开发基于模糊学习模型的交互式挖掘原型系统，建立面向海量空间数据的挖掘和处理平台，研究模糊挖掘算法的实际应用，促进空间co-location模式挖掘技术的实用化进程。

The ever growing need for the application of spatial data has been stimulating research and development of the spatial co-location pattern mining. Just as randomness is inevitable, the existence of fuzziness is also an unavoidable fact on many occasions. For example, the measure of user's interest patterns tends to have varying degrees of fuzziness. In this project, we intend to study fuzzy technologies in spatial co-location pattern mining systematically, including the interestingness metrics and mining methods for spatial co-location patterns based on fuzzy set theory, the interactive fuzzy mining methods of spatial co-location patterns, and fuzzy co-location mining algorithms for massive spatial data. Based on the proposed fuzzy learning models, an interactive mining prototype system will be developed. A mining and processing platform for massive spatial data will be established, and practical applications of fuzzy mining algorithms will be studied. Therefore, the practical process of spatial co-location pattern mining will be promoted.