【摘要】 着眼于由用户数据的极端稀疏性所导致的推荐质量下降问题,基于最近邻算法,将随机抽样算法结合前瞻框架,应用于推荐系统,旨在提高推荐精度。并在此基础上对其进行实验评估,表现出较低的平均误差率和较高的稳定性。更多还原

【Abstract】 The decline of recommending quantity resulted in the extreme sparsity of user data was dealt with,based on nearest neighbor algorithm and the combination of selective sampling and lookahead framework for recommendation system,with the purpose of improving the accuracy of recommendation.The algorithm was put into experiment,with much lower average error rate and higher stability.更多还原