Abstract: The design and application of visual communication system should be human-oriented, but currently this is often ignored by designers, resulting in poor user experience of visual communication. In order to improve the experience effect of visual communication system, combined with the existing computer technology, this paper proposes an intelligent visual communication system for user experience. First, for the problem of extracting multimodal features of users, considering the characteristics of different modal data, long and short-term memory networks are used to extract features with contextual information, and multi-scale convolutional neural networks are used for visual modality to extract low-level features from video frames. In the cross-modal stage, the low-level features in the source modality are used to enhance the target modality features. Then, for the personalized recommendation problem of users, a graph information extractor is constructed based on the graph convolutional neural network to fuse the recommended user-item bipartite graph node neighborhood information and generate a dense vector representation of nodes, which can enhance the recommendation effect in the form of incorporating the graph information representation in the deep recommendation model with Transformer as the sequence feature extractor. The proposed method is experimentally validated to shorten the response time and improve the performance of the system, which can increase the user experience of the visual communication system. The system designed in this article is user experience oriented, combined with Multimodal Features and intelligent recommendation algorithms, effectively meeting the personalized needs of users and has certain practical significance.

Chao Peng, “Design and Application of Intelligent Visual Communication System for User Experience” International Journal of Advanced Computer Science and Applications(IJACSA), 15(8), 2024. http://dx.doi.org/10.14569/IJACSA.2024.01508111

@article{Peng2024,
title = {Design and Application of Intelligent Visual Communication System for User Experience},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.01508111},
url = {http://dx.doi.org/10.14569/IJACSA.2024.01508111},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {8},
author = {Chao Peng}
}