Research on Personalized Service System in E-Supermarket by using Adaptive Recommendation Algorithm
Yanwen Wu, Qi Luo, Min Liu, Zhenghong Wu, Liyong Wan · 2006
To meet the personalized needs of customers in e-supermarket, an adaptive recommendation algorithm based on support vector machine was proposed in the paper. First, the commodities that user needed were classified as several categories through support vector machine, which ensured the recall of commodity recommendation. Then vector space model was used for content-based recommendation, specific commodities in several categories were obtained to ensure the precision. The algorithm had two advantages; the first was that it dealt with complex high dimensional data better, which obtained parameters directly form adaptive learning classifier. The second was that it had a better capability of classification. The algorithm was also used in personalized recommendation service system based on e-supermarket. The system could support e-commence better. The results manifested that the algorithm was effective