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