Application recommending method and apparatus

  • US 9,953,262 B2
  • Filed: 06/03/2016
  • Issued: 04/24/2018
  • Est. Priority Date: 03/28/2014
  • Status: Active Grant
First Claim
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1. An application recommending method, comprising:

  • acquiring a first behavior eigenvalue according to behavior data of a first user;

    determining at least one second user from a user relationship chain of the first payment relationship chain of the first user, a degree of similarity between a second behavior eigenvalue and the first behavior eigenvalue being greater than a preset threshold, and the second behavior eigenvalue being a behavior eigenvalue of the second user;

    determining a to-be-recommended application for the first user on a basis of behavior data of the at least one second user; and

    acquiring a scheduling weight of each compute node before the acquiring a first behavior eigenvalue and computing a system load of the compute node,wherein the system load of the compute node is determined in accordance with;


    Zi=Ri*0.8*α

    +0.2/Ti*β

    ,
    wherein Zi indicates a system load of an ith compute node, Ri indicates a resource utilization of the ith compute node, Ti indicates a computation delay of the ith compute node, and α and

    β

    are both constants.

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