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Categorizing content

  • US 9,405,824 B2
  • Filed: 06/28/2012
  • Issued: 08/02/2016
  • Est. Priority Date: 06/28/2012
  • Status: Expired due to Fees
First Claim
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1. A method for categorizing content comprising:

  • categorizing, by use of a processor, content of a content stream into a category of a plurality of categories, the category selected based on at least a portion of the content corresponding to one or more of a keyword and a key image in a keyword database, the one or more of a keyword and a key image indexed to at least one category of the plurality of categories;

    recording a user-generated navigation action directed to first content of the content stream, the navigation action being selected from the group consisting of a scroll pause, a content selection, a content upload, a content like, and a cursor hover, wherein the navigation action comprises an associated value and timestamp indicating when the navigation action occurred, the associated value for the navigation action being unique to the navigation action such that a value associated with one of the navigation actions is different from a value of another navigation action;

    elevating a ranking of a first category associated with the first content in response to the navigation action, the ranking being determined according to the function;


    R=Σ

    v/t,


    where R is the ranking of the first category, v is a value associated with a navigation action, and t is a time interval since the timestamp indicating when the navigation action occurred such that the ranking is determined as an aggregation of each value for every navigation action associated with the first category and a time interval since the timestamp associated with the navigation action; and

    displaying highest ranking categories, and subcategories of each of the highest ranking categories, for selection, the displayed highest ranking categories being organized into hierarchical levels, each hierarchical level being associated with a range of rankings, wherein the displayed highest ranking categories within each hierarchical level are sorted based on an affinity weight to user friends.

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