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User data sharing method and device

  • US 10,673,979 B2
  • Filed: 05/29/2018
  • Issued: 06/02/2020
  • Est. Priority Date: 12/01/2015
  • Status: Active Grant
First Claim
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1. A user data sharing method, comprising:

  • acquiring information of a query medium, wherein the query medium is a medium for querying a target user account;

    searching and obtaining, according to the information of the query medium, at least one user account related to the query medium and relationship information of the at least one user account from a medium network, the relationship information of the user account comprising;

    a strength of a relationship between the user account and the query medium and a strength of a relationship between the user account and other user accounts, wherein the relationship between the user account and the query medium includes same-occurrence relationship, and the relationship between the user account and the other user accounts includes one or more of social relationship, transaction relationship, shared-device relationship and shared-medium relationship;

    constructing a local medium network by using the obtained at least one user account and the relationship information of the at least one user account, wherein the local medium network comprises a plurality of edges representing relationships between query media and user accounts, and relationships among user accounts, and each of the edges is associated with an edge weight representing a relationship strength score;

    determining a trusted account from the at least one user account by using the local medium network comprising using the local medium network to perform mixed sorting on the at least one user account, and to determine first N of the sorted user accounts as trusted accounts, N being a positive integer, wherein the using the local medium network to perform mixed sorting on the at least one user account comprises;

    normalizing edge weights of the edges in the local medium network;

    performing an iterative calculation on the normalized edge weights until converging;

    calculating a comprehensive weight for each user account by using the edge weights after the converging; and

    sorting the at least one user account according to the comprehensive weights of all user accounts, to determine the trusted account; and

    acquiring user data of the trusted account and outputting the user data of the trusted account as the user data corresponding to the information of the query medium.

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