Automatic Seed Word Selection for Topic Modeling

Topic modeling is widely used to uncover latent semantic topics from a corpus. However, topic models often struggle to identify minor topics due to their tendency to prioritize dominant patterns in the data. They are also hindered by polysemous words and general terms, which frequently appear in mul...

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Bibliographic Details
Main Authors: Dahyun Jeong, Jeongin Hwang, Yunjin Choi, Yoon-Yeong Kim
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10879013/
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