Name
Abstract | ||
|---|---|---|
Redistricting is the process of dividing a geographic area into districts or zones. This process has been considered in the past as a problem that is computationally too complex for an automated system to be developed that can produce unbiased plans. In this paper we present a novel method for redistricting a geographic area using a heuristic-based approach for polygonal spatial clustering. While clustering geospatial polygons several complex issues need to be addressed – such as: removing order dependency, clustering all polygons assuming no outliers, and strategically utilizing domain knowledge to guide the clustering process. In order to address these special needs, we have developed the Constrained Polygonal Spatial Clustering (CPSC) algorithm that holistically integrates do-main knowledge in the form of cluster-level and instance-level constraints and uses heuristic functions to grow clusters. In order to illustrate the usefulness of our algorithm we have applied it to the problem of formation of unbiased congressional districts. Furthermore, we compare and contrast our algorithm with two other approaches proposed in the literature for redistricting, namely – graph partitioning and simulated annealing. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICDM.2009.126 | ICDM |
Keywords | Field | DocType |
clustering process,geographic area,utilizing domain knowledge,order dependency,polygonal spatial clustering,do-main knowledge,heuristic-based polygonal clustering,complex issue,constrained polygonal spatial clustering,unbiased congressional district,unbiased plan,data mining,geographic information systems,polygon,simulated annealing,graph partitioning,algorithm design and analysis,clustering algorithms,shape,domain knowledge | Data mining,Fuzzy clustering,Canopy clustering algorithm,CURE data clustering algorithm,Heuristic,Correlation clustering,Computer science,Artificial intelligence,Constrained clustering,Cluster analysis,Redistricting,Machine learning | Conference |
ISSN | Citations | PageRank |
1550-4786 | 7 | 0.87 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Deepti Joshi | 1 | 62 | 5.55 |
| Leen-kiat Soh | 2 | 592 | 81.43 |
| A Samal | 3 | 1033 | 213.54 |