This paper proposes a text summarization method for the WeChat platform based on improved TextRank, which comprehensively considers user demands and sentence features in the process of summarization. Few studies on improving the information service of the WeChat platform by automatic text summarization. Īt present, the research on health information of WeChat official accounts platform mainly focuses on the influence of the WeChat platform on the rehabilitation of certain diseases, the sharing behavior of health information through WeChat, the promotion of WeChat platform on health information education, and knowledge service improvement method based on label aggregation. The automatic summarization of knowledge resources on the WeChat platform can effectively solve the contradiction between knowledge redundancy and the limited reading ability of users and provide users with high quality and integrated information. Without comments and supplementary explanations, it can summarize the core ideas of the text since the WeChat platform does not specify the format of the information, and many texts do not have introductions or summaries. The summary is a brief and accurate description of the important content of the literature. Therefore, how to identify effective information from a wide range of message push and improve reading efficiency has become an urgent need for WeChat users. There will be a misunderstanding to speculate the content by the title of the text. However, most of the titles of the current articles on the platform are intended to attract attention, while a few titles indicate the theme of the text. The research shows that the user knowledge demands of the WeChat platform are high-quality integrated and rich in knowledge resources, multifunctional beautiful interface, and reliable system, as well as intelligent and personalized service. The total number of articles published by public health WeChat official accounts such as “Dingxiang Doctor,” “Good Doctors,” “Family Doctors,” and “Hua Yi Wang” can reach more than 5 million times per week. WeChat official accounts platform remains China's most iconic mobile application and has quickly become the mainstream media for spreading health knowledge. However, social media addiction can lead to health problems such as burning eyes, headaches, and sleep disorders. In the era of the mobile Internet, social media represented by microblogs, WeChat, and short-form videos has become a part of people's lives. According to the complexity of the algorithm, this method is not suitable for the automatic summarization of long or multiple documents. The improved TextRank method, integrating user demands and sentence features into the model, makes the results of text summarization closer to the theme of the article and more able to meet the user demand. The results show that the TextRank algorithm has obvious hints on the accuracy of text summarization extraction after fusing the Word2vec model. The data source crawled from the Sogou WeChat platform. This paper proposes a text summarization method for the WeChat platform based on improved TextRank that takes into account both user demands and sentence features during the summarization process. If we use the way of artificial recognition to filter information, it will inevitably cause huge labor and time cost, and the effect is very little in front of massive articles. In order to meet the increasingly accurate and efficient knowledge service needs of users, reorganizing and aggregating document knowledge resources is effective. However, the platform information is redundant, miscellaneous, and overloaded. With the rapid development of we-media information dissemination, WeChat official accounts platform has become an important way for people to obtain health related knowledge.
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