Vector-Degree: A General Similarity Measure for Co-location Patterns. - Pingping Wu; Lizhen Wang 001; Muquan Zou (ICBK, 2019)

Discovering Prevalent Weighted Co-Location Patterns on Spatial Data Without Candidates. - Vanha Tran; Lizhen Wang 001; Muquan Zou; Hongmei Chen 003 (APWeb/WAIM (1), 2022)

Mining Type-β Co-Location Patterns on Closeness Centrality in Spatial Data Sets. - Muquan Zou; Lizhen Wang 001; Pingping Wu; Vanha Tran (ISPRS Int. J. Geo Inf., 2022)

A maximal ordered ego-clique based approach for prevalent co-location pattern mining. - Pingping Wu; Lizhen Wang 001; Muquan Zou (Inf. Sci., 2022)

Mining Maximal High Utility Co-location Patterns from Large-Scale Spatial Data. - Muquan Zou; Vanha Tran; Ducanh Khuat; Thanhcong Do; Jinpeng Zhang (DMBD (2), 2023)

Efficiently mining maximal l-reachability co-location patterns from spatial data sets. - Muquan Zou; Lizhen Wang 001; Pingping Wu; Vanha Tran (Intell. Data Anal., 2023)

An Efficient Clique-Based Level-Wise Search Algorithm for Spatial Prevalent Co-location Pattern Mining. - Muquan Zou; Vanha Tran; Thiloan Bui; Hoangan Le; Ducduong Pham (ICAISC (1), 2024)

Efficient Multilevel Spatial Co-location Pattern Discovery Based on Density-Wise Clustering and MC-Hash Structure. - Vanha Tran; Muquan Zou; Thiloan Bui; Thaigiang Do; Ducanh Khuat; Hoangan Le (ICSI, 2024)

MTRM: A Web-Miner Multi-Threshold Mining Co-location Patterns to Mitigate Redundancy. - Muquan Zou; Vanluan Nguyen; Vanha Tran; Ducanh Khuat; Thiloan Bui (WISE (PhD Symposium, Demos and Workshops), 2024)