文章基本信息

标题：Survey on Improvement of Apriori Algorithm
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作者：Dixita Tandel ; Prof. Neha Soni
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2017
卷号：5
期号：1
页码：182
DOI：10.15680/IJIRCCE.2017.0501026
出版社：S&S Publications
摘要：Data mining is the process of analyzing the data from large database and summarizing that data intouseful information. Association rule mining is one of the most important data mining’s functionalities for findingfrequent itemset or association between items or attribute. It can be consider as two step process, first it find frequentitems and from that it generate association rule. Apriori algorithm is the most popular algorithm which is used toextract frequent itemsets from large data sets where these frequent itemsets can be used to generate association rules.These rules are used for discovering knowledge such as detecting unknown relationships, decision making, prediction,etc. It finds frequent itemset based on join and prune step. It’s simple but having some disadvantages such as generatemore candidate itemset, multiple scanning of database, etc. Large number of variations has been proposed in theliterature to overcome the shortcomings of Apriori algorithm. So this paper presents a survey on Apriori algorithm ofrecent research work carried by different researchers with example.
关键词：Data mining; association rule; apriori; support; frequent itemset