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Research and Application of User Behavior Data Analysis Technology for E-commerce

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27 lut 2025

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Figure 1.

Algorithm architecture of recommendation system
Algorithm architecture of recommendation system

Figure 2.

Hierarchical recommendation system model
Hierarchical recommendation system model

Figure 3.

Model feature importance diagram
Model feature importance diagram

Figure 4.

Variation of MAE under different nearest neighbor numbers
Variation of MAE under different nearest neighbor numbers

Figure 5.

Experiment on category number of association rules
Experiment on category number of association rules

Figure 6.

Experimental results for different N values
Experimental results for different N values

Figure 7.

Performance of each algorithm on various indicators
Performance of each algorithm on various indicators

Figure 8.

Average absolute error of each algorithm on the dataset
Average absolute error of each algorithm on the dataset

Figure 9.

Accuracy of each algorithm on the data set
Accuracy of each algorithm on the data set

Figure 10.

User preference classification
User preference classification

Comparison of effects of three models

Model Name Accuracy rate Recall rate F1 Value
Logistic regression 4.25% 4.31% 4.27%
LightGBM 5.61% 5.63% 5.62%
LightGBM + LR 5.81% 602.70% 5.93%

Evaluation indicators of each algorithm

Precision Coverage MAE Diversity Surprise Unexpectedness
CF 16.68% 8.34% 89.11% 0.365 10.956 8.841
CF-FP-NN 23.94% 99.20% 78.68% 0.914 8.130 1.633
ACF-FP-NN 26.40% 99.20% 76.93% 0.936 8.242 1.444

Overall prediction results

Model Name Accuracy rate Recall rate F1
Logistic regression 4.66% 4.72% 4.68%
Język:
Angielski
Częstotliwość wydawania:
1 razy w roku
Dziedziny czasopisma:
Nauki biologiczne, Nauki biologiczne, inne, Matematyka, Matematyka stosowana, Matematyka ogólna, Fizyka, Fizyka, inne