University of Alberta DISCOVERING CO-LOCATION PATTERNS AND RULES IN UNCERTAIN SPATIAL DATASETS

Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatever without the author’s prior written permission. Co-location mining, which focuses on the detection of co-location patterns, is one of the tasks of spatial data mining. A co-location pattern is a set of spatial features frequently located in close proximity of each other. Most previous works are based on transaction-free apriori-like algorithms which use user-defined thresholds and are designed for point objects. Due to the absence of a clear notion of transactions