8. A computer program product comprising at least one non-transitory computer readable medium storing instructions translatable by a server computer implementing a natural language processing system to perform: determining whether a source string is present in a target string, wherein the source string and the target string represent text strings each comprising a sequence of characters that identify a vehicle characteristic, wherein the source string is from a first source communicatively connected to the server computer over a first network connection, wherein the target string is from a second source communicatively connected to the server computer over a second network connection, and wherein the first source and the second source employ different naming conventions for automotive data collected thereby; if the source string is present in the target string, outputting a match containing the source string and the target string; and if the source string is not present in the target string, computing a similarity factor based at least on a first set of parameters, wherein the first set of parameters comprises a Levenshtein edit distance parameter based on a comparison of characters in the source string and the target string, a single-word matches parameter based on a comparison of words in the source string and the target string, and a multi-word matches parameter based on a comparison of successive words in the source string and the target string, the similarity factor representing a measure of similarity between the source string and the target string; wherein the step of determining whether the source string is present in the target string further comprises: determining if an automotive base term that matches the source string is present in an automotive lexicon; utilizing the automotive base term to create a set of strings that includes one or more terms in the automotive lexicon; and comparing each string in the set of strings with the target string; and utilizing the match or the output to find from the first source, the second source, or both pricing information associated with multiple vehicles having a user-selected trim; wherein the pricing information comprises at least one trade-in price, at least one sale price, at least one list price, or a combination thereof; wherein utilizing the match to find pricing information associated with the vehicles having the user-selected trim comprises aggregating sales information from the first and second sources according to the source string, and determining a value of the vehicles having the user-selected trim based on the aggregated sales information; wherein at least a portion of the sales information is aggregated in real time in response to a user selecting the vehicles having the user-selected trim; and wherein the determined value of the vehicles having the user-selected trim is presented to the user and is dynamically updated to reflect at least the portion of the sales information aggregated in real time.
8. A computer program product comprising at least one non-transitory computer readable medium storing instructions translatable by a server computer implementing a natural language processing system to perform: determining whether a source string is present in a target string, wherein the source string and the target string represent text strings each comprising a sequence of characters that identify a vehicle characteristic, wherein the source string is from a first source communicatively connected to the server computer over a first network connection, wherein the target string is from a second source communicatively connected to the server computer over a second network connection, and wherein the first source and the second source employ different naming conventions for automotive data collected thereby; if the source string is present in the target string, outputting a match containing the source string and the target string; and if the source string is not present in the target string, computing a similarity factor based at least on a first set of parameters, wherein the first set of parameters comprises a Levenshtein edit distance parameter based on a comparison of characters in the source string and the target string, a single-word matches parameter based on a comparison of words in the source string and the target string, and a multi-word matches parameter based on a comparison of successive words in the source string and the target string, the similarity factor representing a measure of similarity between the source string and the target string; wherein the step of determining whether the source string is present in the target string further comprises: determining if an automotive base term that matches the source string is present in an automotive lexicon; utilizing the automotive base term to create a set of strings that includes one or more terms in the automotive lexicon; and comparing each string in the set of strings with the target string; and utilizing the match or the output to find from the first source, the second source, or both pricing information associated with multiple vehicles having a user-selected trim; wherein the pricing information comprises at least one trade-in price, at least one sale price, at least one list price, or a combination thereof; wherein utilizing the match to find pricing information associated with the vehicles having the user-selected trim comprises aggregating sales information from the first and second sources according to the source string, and determining a value of the vehicles having the user-selected trim based on the aggregated sales information; wherein at least a portion of the sales information is aggregated in real time in response to a user selecting the vehicles having the user-selected trim; and wherein the determined value of the vehicles having the user-selected trim is presented to the user and is dynamically updated to reflect at least the portion of the sales information aggregated in real time. 13. The computer program product of claim 8 , wherein the single-word matches parameter is computed by: dividing a number of single words present in both the source string and the target string by a total number of words in the target string.