Code, system, and method for generating concepts
First Claim
1. A computer-assisted method for generating candidate novel concepts related to one or more selected classes of concepts, comprising (A) generating strings of terms composed of combinations of word and optionally, word-group terms that are descriptive of concept elements in such class(es), (B) producing one or more high fitness strings by the steps of:
- (B1) mating said strings to generate strings with new combinations of terms;
(B2) determining for each of said strings, a fitness score based on the application of a fitness metric which is related to one or both of the following;
(B2a) for pairs of terms in the string, the number occurrence of such pairs of terms in texts in a selected library of texts;
(B2b) for terms in the string, and for one or more preselected attributes, attribute-specific selectivity values of such terms, (B3) selecting those strings having the highest fitness score, and (B4) repeating steps (B1)-(B3) until a desired fitness-score stability is reached, and (C) identifying one or more texts whose terms overlap with those of a high fitness string produced in step (B).
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Abstract
Disclosed are a computer-readable code, system and method for generating candidate novel concepts in one or more selected fields. The system operates to generate strings of terms composed of combinations of word and optionally, word-group terms that are descriptive of concept elements in such field(s), and uses a genetic algorithm to find one or more high fitness strings, based on the application of a fitness metric which quantifies, e.g., the number occurrence of pairs of terms in texts in a selected library of texts. The highest- score string or strings are then applied in a database search to identify one or more pairs of primary and secondary texts whose terms overlap with those of a high fitness string.
155 Citations
26 Claims
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1. A computer-assisted method for generating candidate novel concepts related to one or more selected classes of concepts, comprising
(A) generating strings of terms composed of combinations of word and optionally, word-group terms that are descriptive of concept elements in such class(es), (B) producing one or more high fitness strings by the steps of: -
(B1) mating said strings to generate strings with new combinations of terms;
(B2) determining for each of said strings, a fitness score based on the application of a fitness metric which is related to one or both of the following;
(B2a) for pairs of terms in the string, the number occurrence of such pairs of terms in texts in a selected library of texts;
(B2b) for terms in the string, and for one or more preselected attributes, attribute-specific selectivity values of such terms, (B3) selecting those strings having the highest fitness score, and (B4) repeating steps (B1)-(B3) until a desired fitness-score stability is reached, and (C) identifying one or more texts whose terms overlap with those of a high fitness string produced in step (B). - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26)
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16. A computer-assisted method for generating combinations of word and optionally, word-group terms that represent candidate novel concepts related to one or more selected classes of concepts, comprising
(A) generating strings of terms composed of combinations of word and optionally, word-group terms that are descriptive of concept elements in such class(es), and (B) producing one or more high fitness strings by the steps of: -
(B1) mating said strings to generate strings with new combinations of terms;
(B2) determining for each of said strings, a fitness score based on the application of a fitness metric which is related to one or both of the following;
(B2a) for pairs of terms in the string, the number occurrence of such pairs of terms in texts in a library of texts;
(B2b) for terms in the string, and for one or more preselected attributes, attribute-specific selectivity values of such terms, (B3) selecting those strings having the highest fitness score, and (B4) repeating steps (B1)-(B3) until a desired fitness-score stability is reached.
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Specification