Title :
Research and Application of Improved Apriori Algorithm to Electronic Commerce
Author_Institution :
Coll. of Comput. Sci. & Technol., Dalian Jiaotong Univ., Dalian, China
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;
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
DOI :
10.1109/DCABES.2012.51
