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Eugene David Pendergraft

Charles Austin Parker

Duane J McCrory

Frederick W Reed

John C Waller

By Priscilla Wallace, Executive

A semiotic decision making system operates to respond, for example, to natural language queries. The system operates independent of the type of symbolic elements in which queries are cast. A training corpus of information in the form of sequential sets of a selected type of element is input to the system and processed by a semiotic processing module to create a knowledge database based upon the lineal relationship of elements within the training corpus. The knowledge database is then used to make decisions relating to queries input in the same type of elements. Accordingly, inputting a French training corpus results in a knowledge base useful in answering French questions. Multiple semiotic processing modules may be used to enhance performance.

Semiotic decision making system for responding to natural language queries and components thereof

A decision making system uses semiotic processing modules to transform a training corpus of information, in the form of sequential sets of symbols, into a knowledge database. The knowledge database is thereafter used to make decisions relating to queries input in the same type of training corpus symbols. In the knowledge base, the system stores data representations of analyses of subsets of the training corpus sets of sequential elements. The knowledge base data representations comprise predicates and elemental and non-elemental acts. An inductive processor recursively processes the training corpus sets by evaluating the relationship and frequency of occurrence of individual elements and sets of elements in the training corpus. After processing of the training corpus is completed, the resultant knowledge base is used to evaluate queries in a performance mode of operation.

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Eugene David Pendergraft