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...

Descripción completa

Detalles Bibliográficos

Autores principales:	Nikhil V. Chandran, V. S. Anoop, S. Asharaf
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	IEEE 2025-01-01
Colección:	IEEE Access
Materias:	Deep word embeddings latent Dirichlet allocation text kernels BERT topic modeling Word2Vec
Acceso en línea:	https://ieeexplore.ieee.org/document/10980292/
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!