5 citations · 10 across the 5 of their papers we have counts for
5 papers
Towards Statistically Significant Taxonomy Aware Co-location Pattern Detection
Subhankar Ghosh, Arun Sharma, Jayant Gupta +1
Given a collection of Boolean spatial feature types, their instances, a neighborhood relation (e.g., proximity), and a hierarchical taxonomy of the feature types, the goal is to fi…
Reducing False Discoveries in Statistically-Significant Regional-Colocation Mining: A Summary of Results
Subhankar Ghosh, Jayant Gupta, Arun Sharma +2
Given a set \emph{S} of spatial feature types, its feature instances, a study area, and a neighbor relationship, the goal is to find pairs a region (), a subset \emph{C}…
Reducing Uncertainty in Sea-level Rise Prediction: A Spatial-variability-aware Approach
Subhankar Ghosh, Shuai An, Arun Sharma +3
Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important becau…
Spatiotemporal Data Mining: A Survey
Arun Sharma, Zhe Jiang, Shashi Shekhar
Spatiotemporal data mining aims to discover interesting, useful but non-trivial patterns in big spatial and spatiotemporal data. They are used in various application domains such a…
SAMCNet for Spatial-configuration-based Classification: A Summary of Results
Majid Farhadloo, Carl Molnar, Gaoxiang Luo +6
The goal of spatial-configuration-based classification is to build a classifier to distinguish two classes (e.g., responder, non-responder) based on the spatial arrangements (e.g.,…