Cargando…
Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis
With the growth of online social network platforms and applications, large amounts of textual user-generated content are created daily in the form of comments, reviews, and short-text messages. As a result, users often find it challenging to discover useful information or more on the topic being dis...
Autores principales: | Albalawi, Rania, Yeap, Tet Hin, Benyoucef, Morad |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861298/ https://www.ncbi.nlm.nih.gov/pubmed/33733159 http://dx.doi.org/10.3389/frai.2020.00042 |
Ejemplares similares
-
Computational Modeling of Stereotype Content in Text
por: Fraser, Kathleen C., et al.
Publicado: (2022) -
Editorial: Deep learning with limited labeled data for vision, audio, and text
por: Orescanin, Marko, et al.
Publicado: (2023) -
Beyond the topics: how deep learning can improve the discriminability of probabilistic topic modelling
por: Al Moubayed, Noura, et al.
Publicado: (2020) -
Dataset construction method of cross-lingual summarization based on filtering and text augmentation
por: Pan, Hangyu, et al.
Publicado: (2023) -
Topic2features: a novel framework to classify noisy and sparse textual data using LDA topic distributions
por: Wahid, Junaid Abdul, et al.
Publicado: (2021)