System and method of semantic correlation of rich content

  • US 7,672,952 B2
  • Filed: 12/26/2006
  • Issued: 03/02/2010
  • Est. Priority Date: 07/13/2000
  • Status: Active Grant
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First Claim
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1. A system to recommend content to a user, comprising:

  • a computer;

    a content of interest to the user stored on the computer;

    a first semantic abstract representing the content of interest stored on the computer, the first semantic abstract including a first plurality of state vectors;

    a second semantic abstract representing a second content, the second semantic abstract including a second plurality of state vectors;

    a semantic abstract comparer to compare the first semantic abstract to the second semantic abstract; and

    a content recommender to recommend the second content if the first semantic abstract is within a threshold distance of the second semantic abstract,wherein;

    a dictionary includes a directed set of concepts including a maximal element and directed links between pairs of concepts in the directed set, the directed links defining “

    is a”

    relationships between the concepts in the pairs of concepts, so that each concept is either a source or a sink of at least one directed link;

    for each concept in the directed set other than the maximal element, at least one chain in the directed set includes a set of directed links between pairs of concepts connecting the maximal element and the concept;

    a basis includes a subset of the chains; and

    each state vector in the first semantic abstract and the second semantic abstract measures how concretely a concept is represented in each chain in the basis by identifying the smallest predecessor in the chain in relation to the concept.

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