RANDOM SAMPLING-BASED COLLECTIVE CLASSIFICATION METHOD AND SYSTEM FOR SYBIL ACCOUNT DETECTION

    公开(公告)号:US20240403389A1

    公开(公告)日:2024-12-05

    申请号:US18491570

    申请日:2023-10-20

    Abstract: Disclosed is a random sampling-based collective classification method and system for Sybil account detection. A random sampling-based collective classification method performed by a collective classification system may include performing a first collective classification using training data; constructing sampled new training data by randomly extracting a portion of the entire nodes based on a label assigned to each node according to a result of performing the first collective classification; performing a second collective classification using the constructed new training data; and applying a posterior score difference of each node computed through the first collective classification and the second collective classification to a prior score of each node to be used for training data at a next iteration.

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