Title :
Design and realization of personalized service in electronic commerce
Author_Institution :
Dept. of Bus., Hebei Univ. of Econ. & Bus., Shijiazhuang, China
Abstract :
Classical collaborative filtering recommendation is the most successful recommendation algorithm in electronic commerce system application. However, along with the continuous increase of site structure, content complexity and user number, data is extremely sparse and the real-time property and recommendation accuracy of algorithm decrease significantly, even no any commodity can be recommended. This paper classifies the users in electronic commerce by collaborative clustering and carries out different page recommendations for different types of users to realize the personalized service in electronic commerce.
Keywords :
electronic commerce; information filtering; classical collaborative filtering recommendation; collaborative clustering; content complexity; electronic commerce system application; page recommendations; personalized service; site structure; user number; Algorithm design and analysis; Business; Clustering algorithms; Collaboration; Electronic commerce; Electronic mail; Filtering algorithms; Information filtering; Information filters; Uniform resource locators; collaborative clustering; electronic commerce; personalized service;
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
DOI :
10.1109/ICCSIT.2009.5234605
