Research And Application Of Fuzzy Multidimensional Association Rules

Today,with the increasing amount of data and the hidden knowledge in data,big data analysis,the world of mathematics needs to be tapped everywhere,the quality of information is invaluable,the mining of big data drives information,and useful information is embedded in In big data,using big data mining to get useful value information will have an impact on many decisions and business relationships.The sheer volume of data has spawned various technologies and research on big data,and the technology inside can provide a simpler means for data support.Data mining algorithms have become a very important direction for researching data information.Using mining techniques to mine association rules,useful information can be obtained from the data.After combining with fuzzy,we can dig out more accurate rules and make a basis for decision-making.After the improvement of a large number of researchers,the association rules can be used not only in the transaction database,but also in the relational database.For different dimensions of the cube,we can dig out useful information.Combining the fuzzy and RFM models,the association rules can be made more precise in a certain field,and provide data support for the subsequent recommendation system and precision marketing.The research direction and work described in this paper are mainly carried out in the following parts:1.After obtaining the data,perform some necessary cleaning on the data,such as removing the outliers,duplicate data,and missing values,and after filling and processing,the data with the correct format content after processing is stored in the database or the data warehouse.2.Research on the multi-dimensional data set,and then build the database system after integrating the data.In order to better process the multi-dimensional data set,we build the data cube and use the RFM calculated value as a dimension in the data cube to build the final required database.Table collection.3.Taking the data of a take-out platform as a data set,the RFM model is added to the user's data,and the data set is improved to mine more accurate recommendations.E-commerce is unstoppable and maps everywhere in life.The ordering industry is also an indispensable part of people's lives.The data of the external sales platform is analyzed.We use two algorithms to mature data mining algorithms and use different data processing operations.Mining the association rules of the cube,and finally getting accurate recommendations for users,recommending businesses and food.