Research and Application of Improved Apriori Algorithm to Electronic Commerce

Author

Yang, Shuo

Author_Institution

Coll. of Comput. Sci. & Technol., Dalian Jiaotong Univ., Dalian, China

fYear

2012

fDate

19-22 Oct. 2012

Firstpage

227

Lastpage

231

Abstract

In order to analyze the shopping habits of consumers and more accurately mine the characteristics of consumption, we hereby have proposed and proved Theorem 1-3 to improve the classical Apriori algorithm, resulting in the reduction of database access. We improved the efficiency in the frequent-item sets-based establishment of strong association rule. With this new design we fulfilled the timely recommendation of related products to customers, reflecting the principle of personalized service in e-shopping.

Keywords

Internet; consumer behaviour; data mining; electronic commerce; retail data processing; association rule; consumer shopping habits analysis; consumption characteristics mining; database access reduction; e-shopping; electronic commerce; frequent-itemsets-based establishment; improved apriori algorithm; personalized service; product recommendation; Algorithm design and analysis; Association rules; Business; Itemsets; Marketing and sales; apriori algorithm; association rule; electronic commerce; frequent itemset;

fLanguage

English

Publisher

ieee

Conference_Titel

Distributed Computing and Applications to Business, Engineering & Science (DCABES), 2012 11th International Symposium on

Conference_Location

Guilin

Print_ISBN

978-1-4673-2630-8

Type

conf

DOI

10.1109/DCABES.2012.51

Filename

6385277