基于数据挖掘技术的移动互联网业务研究

摘要

信息时代的来临使得数据量大幅度提高,对于信息的处理变得炙手可热,数据挖掘能够从庞大的、复杂的、不完整的、有噪声的数据库中提取潜在有用的信息.论文提出了一个基于关联规则和Apriori算法的数据挖掘模式,针对移动互联网时代所储藏的大量数据进行处理和分析,在数据挖掘的关联性规则和Apriori算法的基础上进行了改进,利用SQL对算法进行了优化,处理大量的数据时可以节省算法运行的时间,提高准确性,确保数据的质量,最后对算法进行流程评估,证明该算法方法可行有效,能够节约时间,提高效率,从而帮助决策者做出合理的判断.%The advent of the information age has led to a significant increase in the amount of data,and the processing of infor-mation has become hot,and data mining can extract potentially useful information from large,complex,incomplete,and noisy data-bases.This paper presents a data mining model based on association rules and Apriori algorithm. A large number of data stored in the mobile Internet era are processed and analyzed. Based on the association rules of data mining and Apriori algorithm,SQL is used to optimize the algorithm. Dealing with a large amount of data can save the algorithm running time,improve accuracy,to ensure data quality,Finally,the algorithm is evaluated by the process,which proves that the algorithm is feasible and effective,which can save time and improve the efficiency,so as to help decision makers make reasonable judgments.