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Recommending data based on user and data attributes

  • US 8,996,549 B2
  • Filed: 12/20/2011
  • Issued: 03/31/2015
  • Est. Priority Date: 10/11/2011
  • Status: Active Grant
First Claim
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1. At a computer system including one or more processors, a method for recommending data related to a dataset used within a data processing application, the method comprising:

  • detecting that a user has accessed a dataset within the data processing application as part of performing a specified task;

    deriving one or more source attributes relevant to the accessed dataset, the source attributes derived from one or more of user information for the user, and data information for the dataset;

    identifying one or more target attributes relevant to one or more sets of target data directories or one or more target data services, the one or more sets of target data directories and the one or more target data services being separate from the accessed dataset;

    matching the one or more source attributes relevant to the accessed dataset with the one or more target attributes relevant to the one or more sets of target data directories or the one or more target data services, to determine the desirability of at least one of the one or more sets of target data directories or at least one of the one or more target data services as a source of relevant data for being incorporated into the accessed dataset, wherein matching the one or more source attributes with the one or more target attributes comprises submitting the one or more source attributes to a statistical system based on translation from a high-dimensional attribute space to a lower dimensional space; and

    recommending the at least one set of target data directories or the at least one target data service to the user, as able to be incorporated into the accessed dataset.

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