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Abstract

A text comprehension and retrieval method and apparatus that uses letter-semantic analysis of the micro-syntax, or the syntax between the letters, in two words to measure how much two words are related as to their meanings or the human language concepts they present. Letter-semantic analysis involves assigning numerical values to the letters of a first word and a second word based on the dual characteristics of orientation and category inherent in the letters, and then analyzing those numerical values to identify the semantic relatedness of the letters of the first word to the letters of the second word. A letter semantic-matrix assigns weights to the meaningful letters to allow the application of letter semantic rules to convert the concepts represented by the letters of the words to numeric values. The numeric values represent the amount of relatedness of the first word to the second word and are used to retrieve text from documents having concepts related to a user supplied query expression.

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First Claim