Offline and online coupled tensor factorization with knowledge graph.

ABSTRACT: How can we accurately decompose a temporal irregular tensor along while incorporating a related knowledge graph tensor in both offline and online streaming settings? PARAFAC2 decomposition is widely applied to the analysis of irregular tensors consisting of matrices with varying row sizes. In both offline and online streaming scenarios, existing PARAFAC2 methods primarily focus on capturing dynamic features that evolve over time, since data irregularities often arise from temporal variations. However, these methods tend to overlook static features, such as knowledge-based information, which remain unchanged over time. In this paper, we propose KG-CTF (Knowledge Graph-based Coupled Tensor Factorization) and OKG-CTF (Online Knowledge Graph-based Coupled Tensor Factorization), two coupled ten

SUBMITTER: Lee S 

PROVIDER: S-EPMC12611170 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature