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Document Type : Latin Dissertation
Language of Document : English
Record Number : 149263
Doc. No : ET21055
Main Entry : Jeremy Kubica
Title Proper : Efficient Discovery of Spatial Associations and Structure
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : The problem of finding sets of points that conform to a given underlying spatial model is aconceptually simple, but potentially expensive, task that arises in a variety of domains. Thegoal is simply to find occurrences of known types of spatial structure in the data. However,as we begin to examine large, dense, and noisy data sets the cost of finding such occurrencescan increase rapidly.In this thesis I consider the computational issues inherent in extracting model-basedspatial associations and structure from large amounts of noisy data. In particular, I discussthe development of new techniques and algorithms that mitigate or eliminate these compu-tational issues. I show that there are.
Subject : Electericl tess
: برق
electronic file name : TL44203.pdf
Title and statement of responsibility and : Efficient Discovery of Spatial Associations and Structure [Thesis]
 
 
 
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