Link prediction based on hybrid influence of neighbors
In previous link prediction researches, most scholars evaluate the influence of endpoints by the degree or H-index of endpoints, resulting in limited prediction accuracy. Through abundant investigations, we can evaluate the influence of endpoints accurately by the hybrid influence of neighbor nodes....
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Veröffentlicht in: | International journal of modern physics. B, Condensed matter physics, statistical physics, applied physics Condensed matter physics, statistical physics, applied physics, 2020-02, Vol.34 (5), p.2050018 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In previous link prediction researches, most scholars evaluate the influence of endpoints by the degree or H-index of endpoints, resulting in limited prediction accuracy. Through abundant investigations, we can evaluate the influence of endpoints accurately by the hybrid influence of neighbor nodes. Meanwhile, we calculate the hybrid influence of neighbors (HIN) by the average values of degree and H-index. In the paper, we conceive a HIN model. Large-scale experiments on 12 real datasets indicate that the conceived methods can significantly enhance the accuracy of link prediction. |
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ISSN: | 0217-9792 1793-6578 |
DOI: | 10.1142/S0217979220500186 |