LDAViewer: An Automatic Language-Agnostic System for Discovering State-of-the-Art Topics in Research Using Topic Modeling, Bidirectional Encoder Representations From Transformers, and Entity Linking

LDAViewer: An Automatic Language-Agnostic System for Discovering State-of-the-Art Topics in Research Using Topic Modeling, Bidirectional Encoder Representations From Transformers, and Entity Linking

Advancements in knowledge are pivotal to academic progress, necessitating efficient methods for discovering the state-of-the-art in various fields. Existing approaches, however, are language-specific and lack automation, limiting their efficacy. This study aims to develop a language-agnostic softwar...

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Bibliographic Details
Main Authors: Timothy Dillan, Dhomas Hatta Fudholi
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Topic modeling
state-of-the-art discovery
development of knowledge
latent-dirichlet allocation
bidirectional encoder representations from transformers
entity linking
Online Access:https://ieeexplore.ieee.org/document/10147827/

Internet

https://ieeexplore.ieee.org/document/10147827/

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