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Assisted learning for document classification

  • US 9,342,795 B1
  • Filed: 06/05/2013
  • Issued: 05/17/2016
  • Est. Priority Date: 06/05/2013
  • Status: Active Grant
First Claim
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1. A method comprising steps of:

  • querying a user to identify one or more true positive documents in relation to a sample document;

    querying the user to identify a document repository that contains documents similar to the sample document;

    implementing a document classification algorithm to;

    analyze a collection of documents within the document repository to identify a set of multiple documents corresponding to the sample document, wherein said analyzing comprises parsing the collection of documents within the document repository to the set of documents based on one or more keywords present in the sample document and in each document of the set;

    present at least a portion of the set of multiple documents to the user for user classification, wherein said user classification comprises manual classification of each document in the at least a portion of the set of multiple documents as one of (i) a true positive document in relation to the sample document and (ii) a false positive document in relation to the sample document;

    calculating a confidence measure based on the user classification of the at least a portion of the set of multiple documents, wherein said confidence measure corresponds to a level of accuracy by which the document classification algorithm detects one or more documents related to the sample document as compared to the user classification;

    querying the user as to whether the document classification algorithm is to be deployed based on sufficiency of the calculated confidence measure, as determined by the user; and

    deploying the document classification algorithm upon an affirmative response from the user in response to said querying as to whether the document classification algorithm is to be deployed;

    wherein the steps are carried out by at least one computer device.

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