Research On Association Rule Algorithm And Its Application In Intelligent Community Service System

With the rapid development of a series of technologies,such as Internet,Internet of things,information technology,and so on,today's society has entered the era of big data.In the era of big data,how to excavate data effectively and extract the hidden association rules has always been a very active research topic.Traditional association rules algorithm is based on static data,and the association rules that are excavated are highly redundant.However,in practical applications,data for mining is not static,and too many redundant association rules consume much memory space.Therefore,it is of great practical significance to study the association rules algorithm based on non-static data and its application.The main research work in this thesis is as follows:(1)according to the related literature,the basic theory of association rule algorithm is reviewed.The classical association rules algorithm Apriori and FP-growth are mainly studied,and their respective advantages and disadvantages are analyzed.(2)the limitation of the original evaluation criteria of the association rules is analyzed,and the concept of correlation is introduced.(3)the incremental updating algorithm QAIS and NewQAIS are studied,the instances of QAIS and NewQAIS are illustrated,and the Im-NewQAIS algorithm based on QAIS and NewQAIS algorithm is proposed.(4)the storage method of association rules is studied,and an improved relational table storage method is proposed.(5)a set of intelligent community service system is designed and implemented,and the association rule algorithm is applied to the community O2 O module in the system.The Im-NewQAIS algorithm uses hash table to store the item set,adopts the "supportconfidence-relevance" evaluation criteria,and fully considers the data adds,deletion and modification,which effectively solving the problem of association rules and data update synchronization,avoiding the contradiction between the positive and negative association rules,and reducing redundant association rules and saving the storage space.In this thesis,Im-NewQAIS algorithm is applied to the community O2 O module in Intelligent community service system,by analyzing the online consumption data of community owners,the users' consumption characteristics are given,which providing decision support for the analysis of the consumption mode of the system.