Title :
FP-Growth Apriori Algorithm´s Application in the Design for Individualized Virtual Shop on the Internet
Author_Institution :
Nanchang Univ., Nanchang
Abstract :
This paper firstly points out there are two deficiencies of traditional apriori algorithm; Secondly it introduces an improved aprior algorithm so called FP-growth apriori algorithm that will help resolve two neck-bottle problems of traditional apriori algorithm and has more efficiency than original one. Lastly, based on huge consumers´ data from a famous business website of book, this paper applies FP-growth apriori algorithm to design individualized virtual shop on the Internet. The individualized virtual shop can not only help to realize one-to-one marketing strategy, increase purchasing interest and loyalty of the consumer to virtual shop, but also make virtual shop gains more profit and more competitiveness. Designing an individualized virtual shop on the Internet is an interesting and tough international topic and applying FP-growth apriori algorithm to design individualized virtual shop on the Internet is novel ideal and method. As a result, the research result in this paper is just for reference.
Keywords :
Internet; electronic commerce; marketing; punching; Internet; business Website; individualized virtual shop; one-to-one marketing strategy; purchasing interest; purchasing loyalty; Algorithm design and analysis; Association rules; Books; Cybernetics; Data mining; Internet; Machine learning; Machine learning algorithms; Software algorithms; Uniform resource locators; Apriori; FP-growth; Individualize; Internet; Virtual shop;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370808