Research Article
Dealing with Pure New User Cold-Start Problem in Recommendation System Based on Linked Open Data and Social Network Features
Table 8
F1 measures and the precision values for different top-N recommendations (MovieLens dataset).
| Top N | Proposed system | Method A | Method B | Method C | Method D | Precision | F1 metric | Precision | F1 metric | Precision | F1 metric | Precision | F1 metric | Precision | F1 metric |
| Top-5 | 0.803 | 0.813 | 0.787 | 0.797 | 0.771 | 0.773 | 0.719 | 0.721 | 0.564 | 0.583 | Top-10 | 0.806 | 0.817 | 0.796 | 0.807 | 0.782 | 0.784 | 0.736 | 0.739 | 0.582 | 0.601 | Top-15 | 0.822 | 0.832 | 0.816 | 0.827 | 0.802 | 0.804 | 0.747 | 0.749 | 0.592 | 0.615 | Top-20 | 0.833 | 0.844 | 0.821 | 0.833 | 0.809 | 0.811 | 0.757 | 0.76 | 0.601 | 0.622 | Top-25 | 0.846 | 0.857 | 0.833 | 0.844 | 0.823 | 0.825 | 0.769 | 0.77 | 0.628 | 0.65 | Top-30 | 0.839 | 0.849 | 0.831 | 0.84 | 0.819 | 0.821 | 0.757 | 0.762 | 0.603 | 0.605 | Top-35 | 0.832 | 0.843 | 0.823 | 0.832 | 0.806 | 0.808 | 0.75 | 0.751 | 0.581 | 0.59 | Top-40 | 0.829 | 0.84 | 0.819 | 0.83 | 0.801 | 0.803 | 0.739 | 0.741 | 0.573 | 0.579 | Top-45 | 0.821 | 0.835 | 0.818 | 0.827 | 0.793 | 0.795 | 0.733 | 0.732 | 0.556 | 0.558 | Top-50 | 0.819 | 0.832 | 0.813 | 0.822 | 0.783 | 0.785 | 0.723 | 0.722 | 0.541 | 0.546 |
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