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Scalable Sprase Bayesian Nonparametric and Matrix Tri-factorization Models for Text Mining Applications
Hierarchical Bayesian Models and Matrix factorization methods provide an unsupervised way to learn latent components of data from the grouped or sequence data. For example, in document data, latent component corn-responds ...
Efficient Frequent Closed Itemset Algorithms With Applications To Stream Mining And Classification
Data mining is an area to find valid, novel, potentially useful, and ultimately understandable abstractions in a data. Frequent itemset mining is one of the important data mining approaches to find those abstractions in ...