Application of image sentiment analysis in cross-modal semantics
Qingzhong Zhou · 2022
With the advent of the era of big data, in order to actively cope with the massive and unstructured "information overload", recommendation systems are widely used in network products and have a profound impact on people's lives. At present, the research of recommendation system has been developed for more than ten years, but many of them are still in the incomplete stage, there are problems such as sparse data, insufficient mining of user implicit preferences, and inaccurate semantic description of item features. These pictures, videos and other content are full of users' emotions, which contain a lot of user emotions, which need further Excavation and application, resulting in huge social and economic benefits. However, there are few researches on sentiment analysis of this kind of information, and the multi-modal sentiment analysis of text, images and other information is particularly weak. Multimodal information has the same emotional characteristics and can describe the user's emotional changes from different angles, so as to obtain more accurate emotional identification.