A Knowledge-Driven Approach to Enhance Topic Modeling with Multi-Modal Representation Learning-Reference-Cited by-同舟云学术

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A Knowledge-Driven Approach to Enhance Topic Modeling with Multi-Modal Representation Learning

Published:2024-05-30 Issue: Volume:30 Page:1347-1355
ISSN:
Container-title:Proceedings of the 2024 International Conference on Multimedia Retrieval
language:
Short-container-title:

Author:

Mu Hongzhang¹^ORCID,Zhang Shuili¹^ORCID,Xu Hongbo²^ORCID

Affiliation:

1. Institute of Information Engineering, Chinese Academy of Sciences & School of Cyber Security, University of Chinese Academy of Sciences, Beijing, Beijing, China

2. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, Beijing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3652583.3658069

Reference42 articles.

1. Multi-feature, multi-modal, and multi-source social event detection: A comprehensive survey

2. CrisisMMD: Multimodal Twitter Datasets from Natural Disasters

3. John Arevalo, Thamar Solorio, Manuel Montes-y Gómez, and Fabio A González. 2017. Gated multimodal units for information fusion. arXiv preprint arXiv:1702.01992 (2017).

4. ViViT: A Video Vision Transformer

5. Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence

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