scholarly journals Interactive Probabilistic Post-Mining of User-Preferred Spatial Co-Location Patterns

2018 ◽  
Author(s):  
Lizhen Wang ◽  
Xuguang Bao ◽  
Longbing Cao
Keyword(s):  
Location Patterns

Inter-Metropolitan Location Patterns of Craft Breweries in the United States

2016 ◽  
Vol 46 (1) ◽  
pp. 115-129 ◽  
Author(s):  
Ralph B. McLAUGHLIN ◽  
Neil REID ◽  
Michael S. MOORE
Keyword(s):  
United States ◽  
The United States ◽  
Location Patterns

scholarly journals A Framework for Modelling Economic Regional Location Processes Under Uncertainty

2021 ◽  
Author(s):  
Roy Cerqueti ◽  
Eleonora Cutrini
Keyword(s):  
Theoretical Model ◽  
Theoretical Analysis ◽  
Site Selection ◽  
Decision Problem ◽  
Stochastic Theory ◽  
Spatial Location ◽  
Probabilistic Framework ◽  
Location Patterns ◽  
Regional Location ◽  
Quantitative Tool

AbstractThis paper deals with the theoretical analysis of the spatial concentration and localization of firms and employees over a set of regions. In particular, it provides a simple site-selection theoretical model to describe the probabilistic framework of the location patterns. The adopted quantitative tool is the stochastic theory of urns. The model moves from the empirical evidence of the deviation of the spatial location of companies from the uniform distribution and of employees from the distribution of firms. Factors leading to such deviations are taken into consideration. Specifically, we formalize a decision problem grounded on the economic attributes of the regions and also on the distribution of the existing firms and employees in the territory. To our purpose, the site-selection model is presented as a stepwise process.

Mining Non-Redundant Co-Location Patterns

2021 ◽  
pp. 1-14
Author(s):  
Xuguang Bao ◽  
Jinjie Lu ◽  
Tianlong Gu ◽  
Liang Chang ◽  
Zhoubo Xu ◽  
...  
Keyword(s):  
Location Patterns

scholarly journals Mining Co-Location Patterns with Rare Events from Spatial Data Sets

2006 ◽  
Vol 10 (3) ◽  
pp. 239-260 ◽  
Author(s):  
Yan Huang ◽  
Jian Pei ◽  
Hui Xiong
Keyword(s):  
Spatial Data ◽  
Rare Events ◽  
Data Sets ◽  
Location Patterns ◽  
Spatial Data Sets
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