协同过滤算法的研究
比较行方案设计种近似动态算法每次都利用到前计算结果需完全重新计算关于这方面算法研究若取得进展则极大地提高推荐系统效率参 考 文 献[1] Resnick P IakovouN SushakM et al. GroupLens An open architecture for collaborative filtering of netnews[C]. Proc 1994 Computer Supported Cooperative Work Conf Chapel Hill 1994 175-186.[2] Hill W Stead L Rosenstein M et al. Recommending and evaluating choices in a virtual community of use[C]. Proc Conf Human Factors in Computing Systems. Denver 1995 194-201.[3] Breese JS Heckerman D Kadie C. Empirical analysis of predictive algorithms for collaborative filtering[C]. Proc 14th Conf Uncertainty in Artificial Intelligence Madison 1998 43-52.[4] Delgado J Ishii N. Memory-based weighted-majority prediction for recommender systems[C].Proc ACM SIGIR ’99 Workshop Recommender Systems Algorithms and Evaluation 1999.[5] Nakamura A Abe N. Collaborative filtering using weighted majority prediction algorithms[C]. Proc 15th Int’l Conf Machine Learning Madison 1998 395-403.[6] Billsus D Pazzani M. User modeling for adaptive news access[J]. User Modeling and User-Adapted Interaction 2000 102—3 147-180.[7
<<上一页 下一页>>
广州市越秀区图书馆版权所有。
联系电话：020-87673002
本站访问人数：