App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 7

Fuzzy spatial high utility co-location patterns mining based on extended regions

Mei Yuqi1
Luo Chunhu1
Wang Xiaoxuan1,2
Tan Pan1
Xiong Wen1,2
1. School of Information Science and Technology, Yunnan Normal University, Kunming 650500, China
2. Engineering Research Center of Computer Vision and Intelligent Control Technology, Dept. of Education of Yunnan Province, Kunming 650500, China
DOI: 10.19734/j.issn.1001-3695.2025.10.0468

Abstract

Spatial high-utility co-location pattern mining needs to consider both spatial proximity and utility correlation of instances, and serves as a key direction in spatial data mining. Traditional spatial high-utility co-location pattern mining methods have two limitations: first, the standard of using a single distance threshold to determine proximity easily misses potential spatial correlations; second, utility calculation methods all ignore utility differences among instances, which may lead to pseudo high-utility co-location patterns in mining results. To address these issues, a fuzzy spatial high-utility co-location pattern mining method based on extended regions was proposed. The method defined fuzzy proximity under extended regions to refine the judgment mechanism of spatial proximity. Meanwhile, it remeasured the correlation strength between spatial features and established a value matrix among features to achieve utility evaluation. Finally, it designed a targeted fuzzy C-means clustering algorithm to extract and mine fuzzy high-utility co-location patterns. Experimental results show that the proposed method can explore potential correlations between features more deeply. It improves the accuracy and reliability of spatial high-utility co-location pattern mining and provides more scientific support for relevant spatial decisions.

Foundation Support

国家自然科学基金资助项目(62366061,12461104)
云南省基础研究计划项目(202301AU070152,202401AT070133)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.10.0468
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 7

Publish History

[2026-03-23] Accepted Paper

Cite This Article

梅羽齐, 罗纯虎, 王晓璇, 等. 基于扩展区域的模糊空间高效用并置模式挖掘方法 [J]. 计算机应用研究, 2026, 43 (7). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0468. (Mei Yuqi, Luo Chunhu, Wang Xiaoxuan, et al. Fuzzy spatial high utility co-location patterns mining based on extended regions [J]. Application Research of Computers, 2026, 43 (7). (2026-03-24). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0468. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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