Research on cross-modal AIGC-enabled intelligent reading applications

This study proposes a series of strategies and methods for the application of AIGC technology in smart libraries. Build a library AIGC technology system, upgrade the infrastructure, technical models and service models, and create a personalized, barrier-free and multi-scenario application ecosystem. For the combination of AIGC and smart libraries, an exploration of interactive recommended reading is proposed to improve the effect of the recommendation algorithm through the understanding of emotions. The algorithm in this study is compared with other algorithms for experimental verification. The experimental results show that the algorithm can more accurately identify user needs and continuously improve the recommendation effect as the number of interactions rounds increases. Compared with other algorithms, it has significant performance advantages.