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Delaunay triangulation‐based spatial colocation pattern mining without distance thresholds

https://doi.org/10.1002/sam.11457
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/widm.1151openalex-snapshot
A Delaunay diagram‐based Min–Max CP‐Tree algorithm for Spatial Data Analysis
inferredcites →https://doi.org/10.1007/3-540-47724-1_13openalex-snapshot
Discovering Spatial Co-location Patterns: A Summary of Results
inferredcites →https://doi.org/10.1007/3-540-47789-6_105openalex-snapshot
K-Order Neighbor: the Efficient Implementation Strategy for Restricting Cascaded Update in Realm
inferredcites →https://doi.org/10.1007/978-3-642-40683-6_23openalex-snapshot
GPU-Accelerated Collocation Pattern Discovery
inferredcites →https://doi.org/10.1007/s10109-015-0216-4openalex-snapshot
A generic regional spatio-temporal co-occurrence pattern mining model: a case study for air pollution
inferredcites →https://doi.org/10.1007/s10115-012-0506-9openalex-snapshot
Spatial co-location pattern discovery without thresholds
inferredcites →https://doi.org/10.1007/s10115-019-01381-yopenalex-snapshot
Parallel co-location mining with MapReduce and NoSQL systems
inferredcites →https://doi.org/10.1007/s10707-016-0254-1openalex-snapshot
On discovering co-location patterns in datasets: a case study of pollutants and child cancers
inferredcites →https://doi.org/10.1007/s10844-008-0076-1openalex-snapshot
FARICS: a method of mining spatial association rules and collocations using clustering and Delaunay diagrams
inferredcites →https://doi.org/10.1007/s10844-013-0280-5openalex-snapshot
Mining regional co-location patterns with kNNG
inferredcites →https://doi.org/10.1016/j.compenvurbsys.2011.02.003openalex-snapshot
An adaptive spatial clustering algorithm based on delaunay triangulation
inferredcites →https://doi.org/10.1016/j.eswa.2015.10.010openalex-snapshot
Spatial co-location pattern mining for location-based services in road networks
inferredcites →https://doi.org/10.1016/j.eswa.2016.07.007openalex-snapshot
A fast space-saving algorithm for maximal co-location pattern mining
inferredcites →https://doi.org/10.1016/j.eswa.2017.10.025openalex-snapshot
Efficient spatial co-location pattern mining on multiple GPUs
inferredcites →https://doi.org/10.1016/j.ins.2009.05.023openalex-snapshot
An order-clique-based approach for mining maximal co-locations
inferredcites →https://doi.org/10.1016/j.ins.2018.01.011openalex-snapshot
Effective lossless condensed representation and discovery of spatial co-location patterns
inferredcites →https://doi.org/10.1016/j.ins.2018.09.016openalex-snapshot
Parallel approach to incremental co-location pattern mining
inferredcites →https://doi.org/10.1016/j.patrec.2008.01.028openalex-snapshot
Effective clustering and boundary detection algorithm based on Delaunay triangulation
inferredcites →https://doi.org/10.1016/j.proeng.2012.06.332openalex-snapshot
Discovering Co-location Patterns from Spatial Domain using a Delaunay Approach
inferredcites →https://doi.org/10.1023/a:1015279009755openalex-snapshot
Multi-Level Clustering and its Visualization for Exploratory Spatial Analysis
inferredcites →https://doi.org/10.1080/02693799308901979openalex-snapshot
Delaunay triangulations in TIN creation: an overview and a linear-time algorithm
inferredcites →https://doi.org/10.1080/136588100424972openalex-snapshot
Testing local spatial autocorrelation usingk-order neighbours
inferredcites →https://doi.org/10.1080/13658816.2011.594799openalex-snapshot
Exploratory analysis of the interrelations between co-located boolean spatial features using network graphs
inferredcites →https://doi.org/10.1080/13658816.2013.871284openalex-snapshot
Local and global spatio-temporal entropy indices based on distance-ratios and co-occurrences distributions
inferredcites →https://doi.org/10.1109/bigdata.congress.2014.14openalex-snapshot
A Parallel Spatial Co-location Mining Algorithm Based on MapReduce
inferredcites →https://doi.org/10.1109/cit14202.2008openalex-snapshot
2008 8th IEEE International Conference on Computer and Information Technology
inferredcites →https://doi.org/10.1109/icde.2019.00136openalex-snapshot
Fraction-Score: A New Support Measure for Co-location Pattern Mining
inferredcites →https://doi.org/10.1109/icsdm.2011.5969013openalex-snapshot
Mining top-k closed co-location patterns
inferredcites →https://doi.org/10.1109/mdm.2019.00-55openalex-snapshot
Mining Prevalent Co-Location Patterns Based on Global Topological Relations
inferredcites →https://doi.org/10.1109/tbdata.2018.2871062openalex-snapshot
Parallel Grid-Based Colocation Mining Algorithms on GPUs for Big Spatial Event Data
inferredcites →https://doi.org/10.1109/tkde.2006.150openalex-snapshot
A Joinless Approach for Mining Spatial Colocation Patterns
inferredcites →https://doi.org/10.1109/tkde.2013.88openalex-snapshot
Mining Statistically Significant Co-location and Segregation Patterns
inferredcites →https://doi.org/10.1109/tkde.2017.2759110openalex-snapshot
Redundancy Reduction for Prevalent Co-Location Patterns
inferredcites →https://doi.org/10.1137/1.9781611972764.27openalex-snapshot
Discovery of Co-evolving Spatial Event Sets
inferredcites →https://doi.org/10.1145/1032222.1032258openalex-snapshot
A partial join approach for mining co-location patterns
inferredcites →https://doi.org/10.2174/1874133900903020069openalex-snapshot
Efficient Discovery of Spatial Co-Location Patterns Using the iCPI-tree
inferredcites →https://doi.org/10.3233/ida-173752openalex-snapshot
A framework for generating condensed co-location sets from spatial databases
inferredcites →https://doi.org/10.4236/jsea.2010.32018openalex-snapshot
A Novel Spatial Clustering Algorithm Based on Delaunay Triangulation
inferredcites →https://doi.org/10.48550/arxiv.1810.09007openalex-snapshot
Spatial Co-location Pattern Mining - A new perspective using Graph Database

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-48316-5_41openalex-snapshot
Efficiently Discovering Spatial Prevalent Co-location Patterns Without Distance Thresholds
inferred← citeshttps://doi.org/10.1007/978-981-16-7566-9_1openalex-snapshot
Introduction
inferred← citeshttps://doi.org/10.1007/978-981-16-7566-9_2openalex-snapshot
Maximal Prevalent Co-location Patterns
inferred← citeshttps://doi.org/10.1007/978-981-96-0814-0_4openalex-snapshot
An Algorithm for Discovering Prevalent Co-location Patterns with Considering Both Density and Connectivity
inferred← citeshttps://doi.org/10.1007/978-981-96-1024-2_25openalex-snapshot
Improving Spatial Co-location Pattern Mining with Enhanced Neighbor Relationship Measures
inferred← citeshttps://doi.org/10.1007/978-981-99-9040-5_19openalex-snapshot
Spatial Co-location Pattern Mining—A Survey of Recent Trends
inferred← citeshttps://doi.org/10.1007/s41019-024-00256-9openalex-snapshot
Mining Interpretable Regional Co-location Patterns Based on Urban Functional Region Division
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.119253openalex-snapshot
Spatial co-location pattern mining over extended objects based on cell-relation operations
inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e25047openalex-snapshot
Mining significant local spatial association rules for multi-category point data
inferred← citeshttps://doi.org/10.1016/j.jag.2024.104116openalex-snapshot
Revealing association rules within intricate ecosystems: A spatial co-location mining method based on Geo-Eco knowledge graph
inferred← citeshttps://doi.org/10.1109/iccbd-ai65562.2024.00038openalex-snapshot
Research On Rebuilding the ship’s Finite Element Model from Nodal Data With Triangular Mesh Algorithm
inferred← citeshttps://doi.org/10.1109/ijcnn60899.2024.10651236openalex-snapshot
A fast multi-level co-location pattern mining approach based on extended maximal cliques
inferred← citeshttps://doi.org/10.1109/nics54270.2021.9701511openalex-snapshot
An Efficient Algorithm for Mining Maximal Co-location Pattern Using Instance-trees
inferred← citeshttps://doi.org/10.1360/ssi-2022-0004openalex-snapshot
A parallel algorithm for regional co-location mining based on fuzzy density peak clustering
inferred← citeshttps://doi.org/10.32604/iasc.2021.020075openalex-snapshot
Visualization of Reactor Core Based on Triangular Mesh Method
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