In view of the problems that the singular value decomposition method needs to fill the matrix too much,the k-means algorithm is affected by the K value and the shape of the data set is limited,this paper proposes a meth-od combining TimeSVD++with the improved density peak clustering.Firstly,time factor was introduced to construct TIMESVD++model based on SVD++.Secondly,by introducing the similarity coefficient into the Gaussian kernel function,the local density formula in the density peak clustering algorithm was modified.Information entropy was in-troduced to determine the optimal truncation distance,and finally the data sets MovieLens-1M and MovieLens-100k were verified.The experiments showed that the proposed method was superior to other algorithms in MAE,RMSE,Re-call and F1 value indexes.
关键词
时间因子/密度峰值聚类/局部密度/截断距离
Key words
Time factor/Density peak clustering/Local density/Truncation distance
维普
万方数据