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 :
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