Semantic generation mechanism of news images based on Concept-Net

Online news is an important means of disseminating information, but some online news texts do not match the content described in the original news pictures, and even cause ambiguity among readers. This phenomenon has seriously affected the authority of news and the credibility of news media. In response to this problem, this paper proposes a rich news image description mechanism based on the Concept-Net knowledge graph. The model we provide consists of two parts, namely, extracting the image content and rendering with natural language to generate an accurate description of the news image.