基于 T(X )参与度的负co-location模式挖掘算法  

Negative co-location pattern mining algorithm based on T(X)

作　　者：范莲静 芦俊丽 段鹏[1] 昌鑫 陈书健 FAN Lian-jing;LU Jun-li;DUAN Peng;CHANG Xin;CHENG Shu-jian(Department of Mathematics and Computer Science,Yunnan Minzu University,Kunming 650000,China)

机构地区：[1]云南民族大学数学与计算机科学学院,云南昆明650000

出　　处：《云南民族大学学报（自然科学版）》2023年第1期59-68,共10页Journal of Yunnan Minzu University:Natural Sciences Edition

摘　　要：空间co-location模式是一组在空间中频繁并置的空间特征的子集.负co-location模式从非频繁的空间co-location模式中产生.一般来说很难计算和挖掘频繁的负co-location模式.频繁负co-location模式中有较强的应用价值,如发现外来物种入侵,自然界植被生长规律等.现有对负co-location模式研究不全面且挖掘算法的数量屈指可数.针对该问题,提出了T(X)下的负co-location模式的参与度度量方法,并分析了此度量的合理性、可行性和简便性;其次,利用此度量,可以发现负模式中隐含的“团爆炸”现象,而之前的度量方式不能发现此现象.提出了基于T(X)参与度度量的负co-location模式挖掘算法.最后,实验结果表明,在其他条件不变的情况下,该算法可以挖掘数量更少且更具负相关性的频繁负co-location模式.A spatial co-location pattern is a subset of a set of spatial features that are frequently collocated in space.The negative co-location pattern arises from the infrequent spatial co-location pattern.It is often difficult to calculate and mine frequent negative co-location patterns.The frequent negative co-location model has strong application value,such as the discovery of alien species invasion,natural vegetation growth law,etc.The existing research on negative co-location pattern is incomplete and the number of mining algorithms is very small.Aiming at this problem,firstly,TNPI is proposed,and the rationality,feasibility and simplicity of this measurement are analyzed.Secondly,the phenomenon of“mass explosion”implied in the negative pattern can be found using this metric,which cannot be found in previous measurements.A negative co-location pattern mining algorithm based on T(X)engagement metric is proposed.Finally,experimental results show that the algorithm can mine fewer and more negatively correlated frequent negative co-location patterns without other conditions being constant.

关 键 词：空间数据挖掘 空间co-location模式 负co-location模式 T(X)参与度 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]