Topic-Weighted Kernels: Text Kernels Integrating Topic Weights and Deep Word Embeddings for Semantic Text Analytics

Traditional text classification models, such as text kernels, primarily consider the syntactic aspects of text data. This paper introduces Topic-Weighted Kernels, a new text analytics framework that combines global topical themes with word-level semantics in a text kernel architecture. Three new tex...

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Detalhes bibliográficos

Principais autores:	Nikhil V. Chandran, V. S. Anoop, S. Asharaf
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2025-01-01
coleção:	IEEE Access
Assuntos:	Deep word embeddings latent Dirichlet allocation text kernels BERT topic modeling Word2Vec
Acesso em linha:	https://ieeexplore.ieee.org/document/10980292/
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