DocumentCode
1672037
Title
Personalized Recommendation Algorithm based on SVM
Author
Wu, Bing ; Qi, Luo ; Feng, Xiong
Author_Institution
Wuhan Univ. of Technol., Wuhan
fYear
2007
Firstpage
951
Lastpage
953
Abstract
With the development of the E-commerce, personalized product and service have become a developing trend gradually .To meet the personalized needs of customers in E-commerce, a new personalized 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 was adopted for collaborative recommendation in classification mode, and then Vector Space Model 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. The algorithm could also used in personalized recommendation service system based on E-commerce.
Keywords
electronic commerce; support vector machines; E-commerce; SVM; atomic information; collaborative recommendation; content-based recommendation; personalized recommendation algorithm; support vector machine; vector space model; Algorithm design and analysis; Collaboration; Engineering management; Feedback; Geographic Information Systems; Large-scale systems; Paper technology; Support vector machine classification; Support vector machines; Technology management;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Circuits and Systems, 2007. ICCCAS 2007. International Conference on
Conference_Location
Kokura
Print_ISBN
978-1-4244-1473-4
Type
conf
DOI
10.1109/ICCCAS.2007.4348205
Filename
4348205
Link To Document