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Fig. 8 | EURASIP Journal on Wireless Communications and Networking

Fig. 8

From: Recommendation algorithm based on user score probability and project type

Fig. 8

Comparison of MAE values of two improved algorithms in a data set of train1. It can be seen from the graph that the MAE value of the two algorithms decreases first and then increases, and finally tends to be gentle. With the near neighbor number as the variable, when the near neighbor number is about 40, the MAE values of the two algorithms are the smallest, that is, the error is the smallest. Under the condition of the same neighborhood, the numerical MAE of the UPCF algorithm is lower than the GSCF algorithm. MAE value is smaller, which means that the scoring error of UPCF is lower than GSCF, that is, the recommendation effect of the algorithm UPCF is more accurate than the GSCF algorithm

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