Document classification is a problem in information science. The task is to assign a document to one or more categories, based on its contents. Document classification tasks can be divided into two sorts: supervised document classification where some external mechanism (such as human feedback) provides information on the correct classification for documents, and unsupervised document classification, where the classification must be done entirely without reference to external information.

Document classification techniques include:

• naive Bayes classifier
• latent semantic indexing
• support vector machines

and approaches based on natural language processing.

A recent notable use of document classification techniques has been spam filtering which tries to discern E-mail spam messages from legitimate emails.

See also

• Classification
• Document retrieval
• Information retrieval

External links

• Rafael A. Calvo, Jae-Moon Lee and Xiaobo Li. Managing Content with Automatic Document Classification. Journal of Digital Information, Volume 5 Issue 2, Article No. 282, 2004-06-08
• Introduction to document classification