DocumentCode
461697
Title
Research on Adaptive Recommendation Algorithm in Personalized E-Supermarket Service System
Author
Chen, Jingjing ; Luo, Qi
Author_Institution
Dept. of Inf. Technol., Central China Normal Univ., Wuhan
Volume
3
fYear
2006
fDate
16-20 2006
Abstract
To meet the personalized needs of customers in E-supermarket, a new adaptive recommendation algorithm based on support vector machine was proposed in the paper. First, user profile was organized hierarchically into field information and atomic information needs, considering similar information needs in the group users. Support vector machine (SVM) was adopted for collaborative recommendation in classification mode, and then vector space model (VSM) was used for content-based recommendation according to atomic information needs. The algorithm had overcome the demerit of using collaborative or content-based recommendation solely, which improved the precision and recall in a large degree. It also fits for large scale group recommendation
Keywords
groupware; retail data processing; support vector machines; SVM; adaptive recommendation algorithm; collaborative recommendation; content-based recommendation; customers; personalized E-supermarket service system; support vector machine; vector space model; Collaboration; Feedback; Information technology; Kernel; Large-scale systems; Marketing and sales; Support vector machine classification; Support vector machines; Web page design;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing, 2006 8th International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-9736-3
Electronic_ISBN
0-7803-9736-3
Type
conf
DOI
10.1109/ICOSP.2006.345769
Filename
4129235
Link To Document