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The issues in clustering, the unsupervised classification of patterns, have been addressed in many contexts and by researchers in many disciplines. Its broad appeal and application as one of the steps in exploratory data analysis is well-known. Literature on the pattern clustering methods, algorithms is surveyed. The authors have tried to explore the(More)
This paper describes modular general fuzzy hypersphere neural network (MGFHSNN) with its learning algorithm, which is an extension of general fuzzy hypersphere neural network (GFHSNN) proposed by Kulkarni, Doye and Sontakke (2002) that combines supervised and unsupervised learning in a single algorithm so that it can be used for pure classification, pure(More)
—With the rapid growth of information technology and in many business applications, mining frequent patterns and finding associations among them requires handling large and distributed databases. As FP-tree considered being the best compact data structure to hold the data patterns in memory there has been efforts to make it parallel and distributed to(More)
— Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. This paper proposes a fast k-medoids clustering algorithm which is used for Hybrid Personalized Recommender System (FKMHPRS). The proposed system works in two phases. In the first phase, opinions from the users are(More)