![]() ![]() In this paper, we discuss two different approaches that both simplify the higher-order tensors using coupled low-order factorization models. Unfortunately, the straightforward application of higher-order tensor models becomes problematic, due to the sparsity of the data and due to the complexity of the computations. These models permit the inclusion of context information that is relevant for relation prediction. There are applications, where models with n-ary relations with n > 3 need to be considered, which is the topic of this paper. A typical application of tensor factorization concerns the temporal development of the relationships between objects. For ternary relations, tensor factorization has become popular. If only a single binary relation is of interest, matrix factorization is typically applied. Factorizing approaches have proven effective in the modeling of these types of relations. An important task in network modeling is the prediction of relationships between classes of objects, such as friendship between persons, preferences of users for items, or the influence of genes on diseases. ![]()
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December 2022
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