11. One or more computer-readable storage media having stored thereupon computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: parsing a text into one or more words; filtering the one or more words into one or more filtered words prior to classification of the text, the filtering comprising: determining an amount of variation of frequencies of appearance of a word of the one or more words across a plurality of categories associated with a pre-constructed spherical space model, a number of dimensions of the spherical space model being equal to a number of the plurality of categories; and filtering the word based at least in part on whether the amount of variation is less than a first variation threshold and greater than a second variation threshold, the second variation threshold being greater than zero; determining a word vector in the spherical space model for each filtered word of the one or more filtered words; determining a distance between a sum of word vectors of the one or more filtered words and a respective category vector of each category of the plurality of categories, determining the distance including accumulating normalized word frequency values of the one or more words to obtain a normalized word vector sum; and classifying the text into one or more categories based at least in part on the determined distance associated with each category, classifying the text including classifying the text into a category corresponding to a largest component of the normalized word vector sum.
11. One or more computer-readable storage media having stored thereupon computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: parsing a text into one or more words; filtering the one or more words into one or more filtered words prior to classification of the text, the filtering comprising: determining an amount of variation of frequencies of appearance of a word of the one or more words across a plurality of categories associated with a pre-constructed spherical space model, a number of dimensions of the spherical space model being equal to a number of the plurality of categories; and filtering the word based at least in part on whether the amount of variation is less than a first variation threshold and greater than a second variation threshold, the second variation threshold being greater than zero; determining a word vector in the spherical space model for each filtered word of the one or more filtered words; determining a distance between a sum of word vectors of the one or more filtered words and a respective category vector of each category of the plurality of categories, determining the distance including accumulating normalized word frequency values of the one or more words to obtain a normalized word vector sum; and classifying the text into one or more categories based at least in part on the determined distance associated with each category, classifying the text including classifying the text into a category corresponding to a largest component of the normalized word vector sum. 12. The one or more computer-readable storage media as recited in claim 11 , wherein the distance between the sum of word vectors of the one or more filtered words and the respective category vector comprises a straight line or a spherical arc.