12. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: access event information associated with an event listing; calculate one or more category probabilities for the event listing using one or more categorization models, respectively, each categorization model calculating a category probability based at least in part on the event information associated with the event listing, each category probability corresponding to a category, the category probability being equal to the probability that the event listing falls within the category; for each category probability greater than or equal to a threshold probability, associate with the event listing the category corresponding to the category probability; and display one or more of the categories associated with the event listing to a user.
12. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: access event information associated with an event listing; calculate one or more category probabilities for the event listing using one or more categorization models, respectively, each categorization model calculating a category probability based at least in part on the event information associated with the event listing, each category probability corresponding to a category, the category probability being equal to the probability that the event listing falls within the category; for each category probability greater than or equal to a threshold probability, associate with the event listing the category corresponding to the category probability; and display one or more of the categories associated with the event listing to a user. 15. The system of claim 12 , wherein one or more categorization models are refined by one or more learning algorithms, the learning algorithms being logistic regression, binary classification, multiclass classification, or maximum likelihood estimation.