14. A system comprising: a) a database b) one or more processors; c) a categorizer, wherein the categorizer is programmed to, when run using the one or more processors, perform a plurality of tasks comprising: i) receive one or more text versions of an input from an external source, wherein the input is associated with a plurality of categories, and wherein each of the text versions of the input from the external source comprises one or more input words; ii) creating one or more input word pairings, wherein each input word pairing comprises an input word from one of the one or more text versions of the input from the external source and a word from a textual description pertaining to one of the plurality of categories associated with the input from the external source, wherein the textual description comprises one or more sentences describing the category which it pertains to; iii) for each of the one or more input word pairings, determining a maximum lexical chain confidence score based at least in part on a semantic distance between the words from the word pairing as indicated in a lexical data source; wherein the maximum lexical confidence score is determined by finding a best lexical chain from plural lexical chains obtained from the lexical data source; iv) based at least in part on the maximum lexical chain confidence scores, determining a plurality of category confidence scores, wherein each category confidence score corresponds to a category associated with the input from the external source; and v) identifying the input from the external source as matching one or more of the associated categories, or as being a no match based at least in part on the plurality of category confidence scores.
14. A system comprising: a) a database b) one or more processors; c) a categorizer, wherein the categorizer is programmed to, when run using the one or more processors, perform a plurality of tasks comprising: i) receive one or more text versions of an input from an external source, wherein the input is associated with a plurality of categories, and wherein each of the text versions of the input from the external source comprises one or more input words; ii) creating one or more input word pairings, wherein each input word pairing comprises an input word from one of the one or more text versions of the input from the external source and a word from a textual description pertaining to one of the plurality of categories associated with the input from the external source, wherein the textual description comprises one or more sentences describing the category which it pertains to; iii) for each of the one or more input word pairings, determining a maximum lexical chain confidence score based at least in part on a semantic distance between the words from the word pairing as indicated in a lexical data source; wherein the maximum lexical confidence score is determined by finding a best lexical chain from plural lexical chains obtained from the lexical data source; iv) based at least in part on the maximum lexical chain confidence scores, determining a plurality of category confidence scores, wherein each category confidence score corresponds to a category associated with the input from the external source; and v) identifying the input from the external source as matching one or more of the associated categories, or as being a no match based at least in part on the plurality of category confidence scores. 15. The system of claim 14 , wherein: a) receiving one or more text versions of the input from the external source comprises receiving a plurality of text versions of a user utterance; b) the plurality of text versions of the user utterance comprise different potential transcriptions of the user utterance; c) determining the plurality of category confidence scores comprises, for each category from the plurality of categories: i) determining a lexical chain confidence score corresponding to that category for each of the one or more text versions of the user utterance; and ii) using a majority voting algorithm and the lexical chain confidence scores for each of the one or more text versions of the user utterance to determine the category confidence score.