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A Spatio-Temporal Approach to Identify Variable Size/Shape Collocation


M.Nagabhushana Rao, Dr. P. Govindarajulu


Vol. 6  No. 9  pp. 223-231


The goal of data mining is to discover nuggets. Spatial data mining discovers collocation rules. Especially in spatial data mining, when spatial data is relatively represented with time series, a spatio-temporal significance is inferred. In this context the collocation rule that is a quintessence for the spatial data, obtains changes to its size and shape with temporal influence. Thus, the changes that occur to the spatial knowledge are the spatio-temporal transactions. Mining the spatio-temporal transactions and determining the various behavioral aspects of collocation is one of the substantial activities of GIS


Spatial Data Mining, Temporal Mining, Spatial Knowledge, Collocation