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
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;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.345769