The Designation And Realization Of The Light-Weight Fake Information Web Clawer

Information demand is the automatic demand of every social person.People who survive and develop in society have group needs,and poor information circulation is a non-social characteristic.Only information can eliminate people's uncertainty.The mobile phone is connected to the Internet,and the information integration enables the mobile phone that people carry with them to become the terminal of the Internet.Compared with the computer,the mobile phone has the advantages of small size,portability,and low price.These advantages make the use of mobile phones more popular.In recent years,with the popularization of smart phones and smart devices,people can obtain information from the Internet more simply and quickly,but the problem is that although the total amount of information obtained by people is increasing,some people cannot Effectively filter out the spoiled information in the information group.In these spam messages,false information and rumor information bear the brunt.The influence of rumors after dissemination is very serious,which will lead to public ethics confusion,public ethical values to be seriously distorted or even replaced,to intensify the irrational mood of the public,and to make the event development be artificially degraded.Therefore,it is necessary to separate false information and rumors from a large number of information groups.The false information filtering system can solve this problem very well.The function implemented by this system is to filter the related network news and filter the false information.The system selects the depth-first strategy to crawl the text,and optimizes the efficiency of the crawling by optimizing the relevant url crawling algorithm and optimizing the system.The system uses the SpringBoot framework for major development,Eureka technology for service registration and discovery operations,Ribbon technology for load balancing configuration,Hystrix port fuse mechanism to secure microservices,and Kafka distributed publish and subscribe messaging system for differentlanguages.The transfer of data to ensure the robustness of the system and reduce the coupling of various services in the system.On the basis of studying a large number of rumors detection related work,the system compares,filters and optimizes the existing detection methods,and finally chooses to use the decision tree to filter the false information.Based on the related attributes of false information,the system extracts the author information,path information,time information,text information and other attributes,and constructs an adaptive decision tree model,which can more accurately judge the falseness of the text.Through the design of the whole system,optimization adjustment and the results of a large number of experiments,the system can provide the crawling of news and the identification of false content.The system also has functionality,reliability and maintainability in actual use.Other nature.