1. A computer system for processing a database having language text records to evaluate their relevance to a predetermined subject of interest, the system comprising: processors for processing instructions and the text records; database storage means for storing the text records in the database; a unique word generator for generating and storing a list of unique words contained in the database; a relevant word generator for generating and storing a list of relevant words including a system user's selections from the stored list of unique words; a modified database generator for generating and storing a modified database, the modified database including the list of relevant words and synonyms, if any, associated with each word in the list of relevant words, whereinafter the unique word generator generates a list of unique words of the modified database; a relevant word table including the list of unique words of the modified database; and means for calculating and storing confidence values associated with each word in the relevant word table, each of the confidence values based on input values from a plurality of personnel other than the system user that reflects their perceptions of a relevance of said each word in the relevant word table to the subject of interest; said means for calculating and storing confidence values including a clustering fuzzy expected value system for determining a membership grade for said each word in the relevant word table; said clustering fuzzy expected value system determining said membership grade for a word in the relevant word table including grouping the confidence values for said word in the relevant word table into a plurality of clusters according to a predetermined formula, determining a mean of all the confidence values for said word in the relevant word table, and determining a plurality of mean confidence values each associated with one of said plurality of clusters of said confidence values.
1. A computer system for processing a database having language text records to evaluate their relevance to a predetermined subject of interest, the system comprising: processors for processing instructions and the text records; database storage means for storing the text records in the database; a unique word generator for generating and storing a list of unique words contained in the database; a relevant word generator for generating and storing a list of relevant words including a system user's selections from the stored list of unique words; a modified database generator for generating and storing a modified database, the modified database including the list of relevant words and synonyms, if any, associated with each word in the list of relevant words, whereinafter the unique word generator generates a list of unique words of the modified database; a relevant word table including the list of unique words of the modified database; and means for calculating and storing confidence values associated with each word in the relevant word table, each of the confidence values based on input values from a plurality of personnel other than the system user that reflects their perceptions of a relevance of said each word in the relevant word table to the subject of interest; said means for calculating and storing confidence values including a clustering fuzzy expected value system for determining a membership grade for said each word in the relevant word table; said clustering fuzzy expected value system determining said membership grade for a word in the relevant word table including grouping the confidence values for said word in the relevant word table into a plurality of clusters according to a predetermined formula, determining a mean of all the confidence values for said word in the relevant word table, and determining a plurality of mean confidence values each associated with one of said plurality of clusters of said confidence values. 3. The system according to claim 1, further comprising: a clustering fuzzy evaluator for calculating and storing a clustered fuzzy expected value for each record in the database, wherein the membership grades are grouped into clusters according to the predetermined formula, and wherein the clustered fuzzy expected value for each record in the database is calculated based on a mean of the membership grades for all words in the list of relevant words and on each mean of the membership grades in each of said clusters.