Efficiently mining spatial co-location patterns utilizing fuzzy grid cliques
Spatial co-location pattern (SCP) mining discovers subsets of spatial feature types whose
objects frequently co-locate in a geographic space. Many existing methods treat the space …
objects frequently co-locate in a geographic space. Many existing methods treat the space …
Spatial co-location pattern mining over extended objects based on cell-relation operations
Spatial co-location pattern mining (SCPM) is intended to discover subsets of spatial features
whose instances are frequently located together in geographic areas. Traditional SCPM …
whose instances are frequently located together in geographic areas. Traditional SCPM …
Spatial Co-location Pattern Mining Based on Fuzzy Neighbor Relationship.
MJ Wang, LZ Wang, LH Zhao - Journal of Information …, 2019 - search.ebscohost.com
A co-location pattern is a subset of spatial objects whose instances are frequently located
together in geography space. The traditional co-location mining algorithms treated the …
together in geography space. The traditional co-location mining algorithms treated the …
Spatial colocation pattern discovery incorporating fuzzy theory
X Wang, L Lei, L Wang, P Yang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Spatial colocation patterns are subsets of spatial feature sets that are frequently
“neighboring” in space. In the majority of existing mining methods, neighboring is …
“neighboring” in space. In the majority of existing mining methods, neighboring is …
Mining maximal sub-prevalent co-location patterns
L Wang, X Bao, L Zhou, H Chen - World Wide Web, 2019 - Springer
Spatial prevalent co-location pattern mining is to discover interesting and potentially useful
patterns from spatial data, and it plays an important role in identifying spatially correlated …
patterns from spatial data, and it plays an important role in identifying spatially correlated …
Spatial co-location pattern mining based on density peaks clustering and fuzzy theory
Y Fang, L Wang, T Hu - Web and Big Data: Second International Joint …, 2018 - Springer
Spatial co-location patterns are the subsets of spatial features whose instances are
frequently located together in geographic space. Traditional co-location pattern mining …
frequently located together in geographic space. Traditional co-location pattern mining …
Mining spatial co-location patterns based on overlap maximal clique partitioning
Spatial co-location patterns are groups of spatial features whose instances are frequently
located together in spatial proximity. Most existing algorithms of discovering spatial co …
located together in spatial proximity. Most existing algorithms of discovering spatial co …
KNFCOM-T: a k-nearest features-based co-location pattern mining algorithm for large spatial data sets by using T-trees
Spatial co-location patterns represent the subsets of Boolean spatial features whose
instances often locate in close geographic proximity. The existing co-location pattern mining …
instances often locate in close geographic proximity. The existing co-location pattern mining …
A clique-based approach for co-location pattern mining
X Bao, L Wang - Information Sciences, 2019 - Elsevier
Co-location pattern mining refers to the task of discovering the group of features (geographic
object types) whose instances (geographic objects) are frequently located close together in …
object types) whose instances (geographic objects) are frequently located close together in …
Multi‐scale approach to mining significant spatial co‐location patterns
Spatial co‐location pattern mining aims to discover a collection of Boolean spatial features,
which are frequently located in close geographic proximity to each other. Existing methods …
which are frequently located in close geographic proximity to each other. Existing methods …