Abstract: Author-topic modeling explores relationships among authors, documents, topics, and words. While traditional Bayesian methods extended Latent Dirichlet Allocation (LDA), recent neural ...

Abstract: By modeling global word co-occurrence patterns, topic models aim to uncover the underlying semantic structure of a corpus. However, their effectiveness is often undermined in short texts due ...

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Expert in PEM fuel cell electrochemistry, thermodynamics, and transport phenomena for automotive applications. Deep understanding of membrane electrode assembly (MEA) structure, catalyst layers, and ...