Gibbs-BERTopic: A Hybrid Approach for Short Text Topic Modeling
As a rich source of direct user needs, online reviews can be effectively analyzed through topic modeling to uncover user preferences and requirements. However, the short and unstructured nature of online reviews, along with their high dimensionality, noise, and complex semantic structure, poses chal...
Saved in:
| Main Authors: | Yan Zhu, Yueying Liu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10930480/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
BERTopic_Teen: a multi-module optimization approach for short text topic modeling in adolescent health
by: Yiqiang Feng, et al.
Published: (2025-08-01) -
Topic modeling-based prediction of software defects and root cause using BERTopic, and multioutput classifier
by: Devi Priya Gottumukkala, et al.
Published: (2025-07-01) -
Advanced Hierarchical Topic Labeling for Short Text
by: Paras Tiwari, et al.
Published: (2023-01-01) -
A Real-Time Semi-Supervised Log Anomaly Detection Framework for ALICE O<sup>2</sup> Facilities
by: Arnatchai Techaviseschai, et al.
Published: (2025-05-01) -
Mapping the Evolution of Social Innovation in Scientific Publications: A Topic Modelling and Text Mining Approach
by: Godnov Uroš, et al.
Published: (2025-08-01)