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Information life cycle search engine and method

  • US 8,423,565 B2
  • Filed: 12/21/2006
  • Issued: 04/16/2013
  • Est. Priority Date: 12/21/2006
  • Status: Active Grant
First Claim
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1. A method of computerized searching through electronic data collections, represented by databases or data structures in a distributed computer system, to expand a user'"'"'s knowledge about select content represented by one or more predetermined words, characters, images or data objects, with a prioritized hierarchical taxonomic system encompassing some select content, comprising:

  • engaging user-selected filters including one or more contextual filters, one or more semiotic filters, and at least one hierarchical taxonomic filter in said taxonomic system;

    engaging a user-selected first plurality of priorities from said at least one prioritized hierarchical taxonomic filter;

    gathering input data represented by a source document or a data stream, said input data having data elements therein;

    identifying all data elements in said input data with said hierarchical taxonomic system and further identifying data elements representing supplemental select content corresponding to said first plurality of priorities therefrom;

    identifying all data elements in said input data matching said contextual filters and said semiotic filters as further supplemental select content;

    engaging a user-selected divergence search function;

    said divergence search function including identifying unknown words, characters, images or data objects in said source document or data stream with the use of one or more of said contextual filters and said semiotic filters, tagging said unknown words, characters, images or data objects for one of contextual relevancy and hierarchical priority, said unknown words, characters, images or data objects used as negative content filters used to discover said unknown words, characters, images or data objects; and

    searching said data collections with both said supplemental select content data elements and said further supplemental select content and said negative content filters, and gathering supplemental documents based on said divergence function.

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