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Systems and methods for generating and implementing an interactive man-machine web interface based on natural language processing and avatar virtual agent based character

  • US 8,156,060 B2
  • Filed: 02/27/2008
  • Issued: 04/10/2012
  • Est. Priority Date: 02/27/2008
  • Status: Active Grant
First Claim
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1. An interactive virtual agent (avatar) system, comprising:

  • a plurality of databases configured to store at least one of client specific information and non-client specific information;

    internal resources configured to provide access to information sources;

    a character interface configured to receive information from a user, and respond to the user with information based on the received information;

    a knowledge model configured to define relations and connections between a plurality of knowledge bases, which comprise a plurality of knowledge layers that define paths from inputs to responses, wherein the plurality of knowledge bases comprise a combination of a general use knowledge base comprising knowledge layers that are used to determine the composition of a received input and a path leading from a question to answer, a corrective action knowledge base configured to correct mistakes in a received input, a generalization knowledge database configured to draw conclusions based on the parsed input, and a multiplicative knowledge base configured to weight relations between the outputs of various knowledge layers;

    a processing engine comprising a computer processor that can be coupled with the client knowledge database, the basic knowledge database, the internal resources, and the character interface, the processing engine configured to;

    receive input from the character interface;

    parse the input using the knowledge model to determine the content of the input;

    break the parsed input into sentences and words for matching into known notions and words using the knowledge model;

    correct spelling and other mistakes for unmatched words and to weight possible variants of words in the parsed input;

    use relations to transform words in the parsed input into notions and notions into other notions and then degrading the weighting of the transformed notionsdetermine relations that apply to the parsed content;

    perform at least one of deduction, generalization, context expansion and synonym finding on the content using the determined relations;

    using the knowledge model, and at least one of the plurality of databases, the internal resources, and external resources, determine an appropriate response to the input; and

    provide the response to the character input to be output to the user.

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