文献类型：期刊文献

英文题名：Research on association rules mining algorithm based on large data

作者：Liu, Yutang[1]; Zhang, Qin[2]

第一作者：Liu, Yutang

机构：[1] Department of Basic Subjects, Henan Institute of Technology, Xinxiang, Henan, 453002, China; [2] School of Mathematics and Information Science, Xinxiang University, Xinxiang, Henan, 453003, China

第一机构：Department of Basic Subjects, Henan Institute of Technology, Xinxiang, Henan, 453002, China

年份：2017

卷号：32

期号：8

起止页码：229-236

外文期刊名：Revista de la Facultad de Ingenieria

收录：EI(收录号：20174504372500)

语种：英文

外文关键词：Association rules - Forestry - Learning algorithms - Trees (mathematics)

摘要：Data mining is a technique dedicated to data analysis and understanding and to reveal the knowledge contained in data. It has become one of the important goals of the application of information technology in the future. Association rule mining is a fruitful and active branch of data mining, and it is a further research topic for researchers. Faced with large databases, association rules mining needs to be improved in terms of mining efficiency, availability, accuracy, and so on. Therefore, this paper studies the association rule mining algorithm based on large data. The paper introduces the knowledge of large data and the basic knowledge of data mining and the mining theory of association rules, and focuses on the association rules mining algorithm, including the Apriori algorithm and the FP-tree algorithm. In a word, on the basis of analyzing and classifying the existing data mining research results and the prototype system, the paper studies the theory model and algorithm of association rule data mining.