Mining Regional High Utility Co-location Pattern

被引：0

作者：

Xiong, Meiyu ^{[1
]}

Chen, Hongmei ^{[1
,2
]}

Wang, Lizhen ^{[1
,2
]}

Xiao, Qing ^{[1
]}

机构：

[1] Yunnan Univ, Sch Informat Sci & Engn, Kunming, Yunnan, Peoples R China

[2] Yunnan Univ, Yunnan Key Lab Intelligent Syst & Comp, Kunming, Yunnan, Peoples R China

来源：

SPATIAL DATA AND INTELLIGENCE, SPATIALDI 2024 | 2024年 / 14619卷

基金：

中国国家自然科学基金;

关键词：

spatial data mining; co-location pattern; regional co-location pattern; high utility co-location pattern;

D O I：

10.1007/978-981-97-2966-1_8

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A co-location pattern is a set of spatial features whose instances are frequently located together in geo-space. In real world, different instances have different distributions and different values. However, existing methods for mining pattern ignore these differences. In this paper, we propose a novel method for mining regional high utility co-location pattern by considering both instance distribution and value. First, local regions are obtained based on fuzzy density peak clustering. Then, the regional high utility co-location pattern is defined, and an efficient algorithm for mining the patterns in local regions is presented by pruning unpromising patterns. The experiment results show the patterns are meaningful and the mining algorithm is efficient.

引用

页码：97 / 107

页数：11

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