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Course Contents

Index structures R tree, M tree, VA file, etc., Space partitioning versus data partitioning methods; Similarity queries Range search, kNN search, Self join; Retrieval techniques Fagin's Algorithm, Threshold Algorithm, Probabilistic Fagin's; Vector Space embedding, properties; Dimensionality reduction SVD,PCA, Fast Map, Wavelets, Fourier transform, etc.; Distance measures Lp norm, Mahalanobis distance, Kullback Leibler divergence measure, Earth Mover's Distance, etc.; Data compression Wavelets, Fourier, V optimal histograms; 

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