43. The method of claim 42, further comprising the steps of, where a group of languages is identified: generating a characterization of the series of character values indicating the relative frequency of n-grams in the text represented by the series of character values; for each language of the group, retrieving a statistical model of the language indicating the relative frequency of n-grams in text documents in which the language is predominant, and comparing the statistical model for the language to the characterization of the series of character values to obtain a quantitative score for the language reflecting the level of similarity between the statistical model of the language and the characterization of the series of character values; and identifying the language having the largest score as the primary language of the text represented by the series of character values.
42. For a series of character values representing text in one or more languages in accordance with a character set that defines a character value for each represented character glyph, ranges of identified character values being defined for groups of characters that commonly occur in a single language or a group of languages, a method in a computer system for identifying a primary language of the text represented by the series of character values, the method comprising the steps of: for each range, determining the number of character values in the series of character values that are within the range; selecting the range containing the largest number character values in the series of character values; and identifying the language or group of languages in which characters within the selected range commonly occur as the primary language of the text represented by the series of character values.