Date of Award:
5-2009
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Computer Science
Advisor/Chair:
SeungJin Lim
Abstract
Existing spatial co-location algorithms based on levels suffer from generating extra, nonclique candidate instances. Thus, they require cliqueness checking at every level. In this thesis, a novel, spatial co-location mining algorithm that automatically generates co-located spatial features without generating any nonclique candidates at any level is proposed. Subsequently, this algorithm generates fewer candidates than other existing level-wise, co-location algorithms without losing any pertinent information. The benefits of this algorithm have been clearly observed at early stages in the mining process.
Recommended Citation
Lin, Zhungshan, "Optimal Candidate Generation in Spatial Co-Location Mining" (2009). All Graduate Theses and Dissertations. Paper 377.
http://digitalcommons.usu.edu/etd/377
Copyright for this work is retained by the student.