Research And Implementation Of Network Media For Automatic Text Summary

In the Internet era,the number of news exploded,users can not effectively obtain content of internet text information.Automatic text summarization technology can organize language text,which can help people to get information more effectively.The automatic summary technology is discussed at different levels,forming a text report which is clear to the truth description and user's points of view that can improve the quality of user information.This paper proposes a long text automatic summarization technology suitable for web news,to solve the problem of great magnanimity,the content of the disorder.Using the lexical features of web news and web tags,this paper proposes a feature importance decision algorithm,which improves the accuracy of the traditional automatic text summarization technology.On the basis of the automatic summarization of web news,this paper analyzes the reading requirements of users,and puts forward the automatic summary report of news text,improving the integrality and readability.Due to the characteristics of micro blog text and complex social relations,this paper presents an automatic summarization method for short text.This method improves summarization with entity relationship,based on entity relation network generated micro-blog text summarization.Experimental results show that the recall rate and accuracy are improved,and the method can be effectively used to express the short text with complex social relations.This paper designed and implemented a micro blog automatic summarization system for public opinion analysis with need of text summary and data analysis.This system not only can summarize the spread of events,analyze the topic,but also pay attention to the changes of data,distribution characteristics,provide a summary report can help people get information in time,analysis of public opinion quickly.