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Name: Jisu Oh, Shan Huang Date : March 2, 2004 Course : Csci 8715 Professor : Shashi Shekhar Project Outline “Spatial Outlier Detection” 1. Motivation A spatial outlier is a spatially referenced object whose non-spatial attribute values are significantly different from the values of its neighborhood. Identification of spatial outliers can lead to the discovery of unexpected, interesting, and useful spatial patterns for further analysis. The purpose of this project is to build a new class, which can detect spatial outlier in a spatial data set. 2. Related works • • • • • WEKA : a collection of machine learning algorithms for solving real-world data mining problems, which is written in Java. But WEKA can only operate on traditional non-spatial database. A method for detecting spatial outliers in graph data set A simple nested loop algorithm to detect spatial outlier A distance-based detection method; a highly efficient partition-based algorithm A wavelet analysis based approach to detect region outlier 3. Problem Definition • • • • Input : spatial data with x,y coordinator Output: spatial outliers Constraints : definition of spatial outlier and used algorithms to find them Objective : finding outliers of spatial object 4. Methodology Constructing several case studies to look at how exactly find outliers using different spatial data set and comparing efficiencies between two different algorithms 5. Conclusion and Contributions Developing application to find spatial outlier based on WEKA system.