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Several data mining applications such as recommender systems and online advertising involve the analysis of large, heterogeneous dyadic data, where the data consists of measurements on pairs of elements, each from a different set of entities. Independent variables (covariates) are additionally associated with the entities along the two modes and their combination. This paper focuses on developing...
Many data mining applications involve predictive modeling of very large, complex datasets. Such applications present a need for innovative algorithms and associated implementations that are not only effective in terms of prediction accuracy, but can also be efficiently run on distributed computational systems to yield results in reasonable time. This paper focuses on predictive modeling of multirelational...
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