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Improving the DeepWalk Algorithm for Link Prediction In Social Networks

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Abstract

 The increasing growth of social networks has drawn researchers' attention to Link prediction, and it has been used in many fields, including computer science, information science, and anthropology. One of the newest Link prediction methods is Graph embedding methods, which are used to generate a feature vector for each node of the graph and find unknown links. The DeepWalk algorithm is one of the most popular Graph embedding methods that captures the network structure using a Random walk with equal probability. In this paper, a modified version of the DeepWalk algorithm is proposed, which uses a new Random walk model to solve the Link prediction problem. In fact, in the proposed method, the amount of structural similarity and the similarity of important features of nodes are combined. The results show that two nodes are more likely to form a link if they have similar structure and important features. To evaluate the proposed method, experiments have been conducted on five datasets. The test results indicate a relative improvement in the results obtained.

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    APA: Copy

    Mahmoodzadeh, Paria, & Rezvanian, Alireza. (2024). Improving the DeepWalk Algorithm for Link Prediction In Social Networks. INTERNATIONAL CONFERENCE ON WEB RESEARCH. SID. https://sid.ir/paper/1147656/en

    Vancouver: Copy

    Mahmoodzadeh Paria, Rezvanian Alireza. Improving the DeepWalk Algorithm for Link Prediction In Social Networks. 2024. Available from: https://sid.ir/paper/1147656/en

    IEEE: Copy

    Paria Mahmoodzadeh, and Alireza Rezvanian, “Improving the DeepWalk Algorithm for Link Prediction In Social Networks,” presented at the INTERNATIONAL CONFERENCE ON WEB RESEARCH. 2024, [Online]. Available: https://sid.ir/paper/1147656/en

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    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
    مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources
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