Research On Key Technologies For Blockchain-based Service Website Evaluation System

In recent years,the online service industry has experienced rapid growth,transforming the way people live their lives.While experiencing online services,most people rely on the ratings and reviews of other users of virtual products or online services as a reference for their own choices.However,some unscrupulous online service providers inject a large amount of false rating information into the evaluation system by using malicious users to pursue improper benefits.Due to the lack of effective measures to prevent the behavior of these malicious users,the normal operation of the evaluation system is seriously impeded.Therefore,establishing trust on the internet has become one of the primary issues for the healthy development of online services.To address this problem,this article undertakes the following research and work:(1)To address the problem that a large amount of review information is untrue in the traditional evaluation system,two methods are used to reduce the impact of false ratings on the comprehensive rating.First,a weighted scoring algorithm based on user influence is proposed.This algorithm establishes a user influence model by analyzing user behavior,and considers the impact of different users on the score when calculating the comprehensive score,thereby improving the accuracy of the project’s comprehensive score.Secondly,a blockchain-based scoring incentive mechanism is designed to associate the user’s scoring behavior with the user’s interests,and effectively constrain the user’s scoring behavior.The experimental results show that the user influence weighted scoring algorithm can effectively resist the attack of malicious users,and has stronger anti-interference ability than the scoring algorithms adopted by Douban and IMDB websites.At the same time,the experimental results also show that the scoring incentive mechanism can reward users with high influence and punish malicious users with low influence.(2)To address the problems of low user participation and poor quality of user review content in rating systems,this article constructs an evolutionary game model based on a user rating incentive mechanism.From the perspective of evolutionary game theory,this model analyzes the factors that affect the platform’s incentive mechanism strategy and user rating behavior.By analyzing the impact of different parameter changes on the evolution process of both parties under different circumstances,as well as the evolutionary game path and equilibrium point,it provides a scientific basis for the system to develop a reasonable incentive mechanism.Experimental results show that differentiating rewards for users based on their influence can effectively increase user participation and improve the quality of user-reviewed content,thereby promoting the healthy development of the system.(3)To address the problem of data loss and tampering in traditional rating systems that are built on centralized databases,this article designs and implements a rating system based on blockchain and IPFS databases.The system utilizes smart contracts to calculate user influence,project overall ratings,and reward distribution to users,and stores a large amount of review content on IPFS.By doing so,user information is protected to the greatest extent possible,and user participation is encouraged through reasonable reward and punishment measures.