Research On Web News Related Technologies Based On Evolutionary Fuzzy Rules

Now in the era of big data every day will produce a large amount of data,today's people feel is the most powerful social media data of explosive growth,such as our daily news from Web,We Chat,weibo,and various types of industry data,the data quantity of almost beyond existing's ability to store,processing and analysis tools.Among them,Web news has become one of the best media for people to keep up with the ever-changing current affairs and obtain the latest information.In the face of these mass news,people simply cannot get the information they need by reading all the news online,especially for some enterprises and individuals with great demand for information.Therefore,in recent years,the research on automatic picking has become a focus of people's attention.On the one hand,it can solve the problem of information overload on the Internet and simplify the information acquired by users.On the other hand,it can help users quickly obtain the information they need according to the needs of users and improve people's reading efficiency.This paper studies the orientation of news text summarization technology,on the basis of summarizing predecessors' research results,to solve the recognition and extraction of the Web news Web page content,the characteristics of the news text analysis and extraction,weight distribution of news text characteristic and the fuzzy logic system in automatical summarization in this paper.The work and research results of this paper mainly include the following aspects:1.In this paper,the structure and semantics of news text are analyzed in depth,the elements of news text summary are defined,the technical framework of automatic summary for news text is put forward,and the key technologies involved are discussed.2.The automatic summarization technology for Web news content is studied.A Web news content recognition and extraction method based on DOM tree is proposed,and the feature item extraction and importance determination algorithm of news text are discussed in detail according to the special structural characteristics of news text,and a new vocabulary feature and sentence feature for news text summary are proposed.3.Fuzzy logic is a powerful tool to describe and deal with the fuzziness of things and the uncertainty in the system.In this paper,fuzzy logic rules and genetic algorithm are combined to improve the quality of news summary generation.4.This paper discusses the polishing and modification of the abstract.Through the experimental analysis of the proposed news text summarization algorithm,it is proved that it has a good effect on news text summarization and can basically meet the current application requirements.