Date of Award:
Master of Science (MS)
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.
Lin, Zhongshan, "Optimal Candidate Generation in Spatial Co-Location Mining" (2009). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 377.
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