The Exploration Of Association Rules In The Recommendation Of Public Service Systems For Government Websites

With the rapid growth of data on the Internet,e-government websites have massive information,but it is difficult for users to find the information they really need,users become clueless in the face of massive and miscellaneous data.At present,there are three ways to solve the problem of information overload:classified directory,search engine and recommendation system.Classified directory websites can only cover a few popular information,and the results of search engines are difficult to meet the needs of users.Therefore,we can see that recommendation system has irreplaceable advantages in government service compared with classified directory and search engine.Therefore,in order to solve the government affairs website to recommend the government affairs service system entrance to users,this paper carried out relevant research,mainly including the following contents:At the beginning of this paper,the research background,problems and research significance are introduced.Several widely used algorithms in the recommendation system are introduced,and then the Apriori algorithm of association rules is selected as the target for further discussion.Secondly,the basic principle and application of association rules are introduced,the basic idea and implementation steps of Apriori algorithm are clarified,and the algorithm is analyzed to further determine its applicability to the recommendation service of government websites.Finally,based on the data set of desensitization application of some qualification exams and professional title review committee from 2015 to 2021 obtained in this study,this data set is applied to the Apriori algorithm to obtain the recommended results of the algorithm.This paper expounds the function of Apriori algorithm in government affairs website application recommendation.