16. A system comprising a process coupled to a computer-readable memory device which stores computer-executable instructions that are executed by the processor and that perform a method of predicting whether character strings refer to a same subject matter, the method comprising: referencing in a database a plurality of character strings that are combinable into pairs of character strings and that are included in a set of text documents; determining an inverse document-frequency value of each character string, wherein each inverse document-frequency value describes an inverse measure of a number of occurrences of a respective character string in the set of text documents; using the computing device to conduct an analysis of the plurality of character strings with a kernel-based classifier, which applies to the plurality of character strings a first kernel function, (1) wherein the first kernel function comprises mathematical combination of a first IDF of a character string included in the first character string, a second IDF of a character string included in the second character string, and a value quantifying a measure of similarity; and (2) wherein based on the analysis, the kernel-based classifier determines a prediction algorithm, which is usable to determine whether two character strings include a similar set of characters; and using the computing device to calculate a prediction value, which quantifies a likelihood that the first character string and the second character string refer to the same subject matter, by applying the prediction algorithm to the two character strings.
16. A system comprising a process coupled to a computer-readable memory device which stores computer-executable instructions that are executed by the processor and that perform a method of predicting whether character strings refer to a same subject matter, the method comprising: referencing in a database a plurality of character strings that are combinable into pairs of character strings and that are included in a set of text documents; determining an inverse document-frequency value of each character string, wherein each inverse document-frequency value describes an inverse measure of a number of occurrences of a respective character string in the set of text documents; using the computing device to conduct an analysis of the plurality of character strings with a kernel-based classifier, which applies to the plurality of character strings a first kernel function, (1) wherein the first kernel function comprises mathematical combination of a first IDF of a character string included in the first character string, a second IDF of a character string included in the second character string, and a value quantifying a measure of similarity; and (2) wherein based on the analysis, the kernel-based classifier determines a prediction algorithm, which is usable to determine whether two character strings include a similar set of characters; and using the computing device to calculate a prediction value, which quantifies a likelihood that the first character string and the second character string refer to the same subject matter, by applying the prediction algorithm to the two character strings. 20. The system of claim 16 , wherein the method further comprises: if the prediction value is at least one of equal to or greater than zero, associating in the database the two different character strings as matches; and if the degree-of-similarity value is less than zero, associating in the database the two different character strings as nonmatches.