Year: 2025
Type: article
Abstract: As an emerging media format, short videos have become an important means for people to obtain information and entertainment. However, the complexity and diversity of short video content pose significant challenges for data analysis. This paper provides a reference for short video data analysis research by investigating multimodal data feature extraction, emotion recognition, and user interest prediction. Firstly, this study explores multimodal data feature extraction methods, utilizing deep learning models to extract image, audio, and textual features. Secondly, an emotion recognition method based on a user feature-guided attention mechanism is proposed, which enhances the feature representation of emotional analysis by fusing multimodal features. Finally, a user interest prediction model is designed by integrating multimodal features and user interest evolution patterns.
Source: Scientific Journal of Technology
DOI: 10.54691/x5jv3760
Author: Yue Xie
Institution: Wenzhou Polytechnic
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411510993