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Matrix Factorizatio...
Abstract
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- We study a matrix factorization problem, that is, to find two factor matrices U and V such that R approximate to U-T x V, where R is a matrix composed of the values of the objects O-1, O-2, ... , O-n at consecutive time points T-1, T-2, ... , T-t. We first present MAFED, a constrained optimization model for this problem, which straightforwardly performs factorization on R. Then based on the interplay of the data in U,V, and R, a probabilistic graphical model using the same optimization objects is constructed, in which structural dependencies of the data in these matrices are revealed. Finally, we present a fitting algorithm to solve the proposed MAFED model, which produces the desired factorization. Empirical studies on real-world datasets demonstrate that our approach outperforms the state-of-the-art comparison algorithms.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
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