Editing Document classification (section)

== Applications ==
Classification techniques have been applied to
* [[spam filter]]ing, a process which tries to discern [[E-mail spam]] messages from legitimate emails
* email [[routing]], sending an email sent to a general address to a specific address or mailbox depending on topic<ref>Stephan Busemann, Sven Schmeier and Roman G. Arens (2000). [https://arxiv.org/abs/cs/0003060 Message classification in the call center]. In Sergei Nirenburg, Douglas Appelt, Fabio Ciravegna and Robert Dale, eds., Proc. 6th Applied Natural Language Processing Conf. (ANLP'00), pp. 158–165, ACL.</ref>
* [[language identification]], automatically determining the language of a text
* genre classification, automatically determining the genre of a text<ref>{{Citation| last1 = Santini| first1 = Marina| last2 = Rosso| first2 = Mark| title = Testing a Genre-Enabled Application: A Preliminary Assessment| url = http://www.bcs.org/upload/pdf/ewic_fd08_paper7.pdf| series = BCS IRSG Symposium: Future Directions in Information Access| place = London, UK| pages = 54–63| year = 2008| access-date = 2011-10-21| archive-date = 2019-11-15| archive-url = https://web.archive.org/web/20191115061125/https://www.bcs.org/upload/pdf/ewic_fd08_paper7.pdf| url-status = dead}}</ref>
* [[Readability|readability assessment]], automatically determining the degree of readability of a text, either to find suitable materials for different age groups or reader types or as part of a larger [[text simplification]] system
* [[sentiment analysis]], determining the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document.
* health-related classification using social media in public health surveillance <ref>X. Dai, M. Bikdash and B. Meyer, "From social media to public health surveillance: Word embedding based clustering method for twitter classification," SoutheastCon 2017, Charlotte, NC, 2017, pp. 1-7.
{{doi|10.1109/SECON.2017.7925400}}</ref>
* article triage, selecting articles that are relevant for manual literature curation, for example as is being done as the first step to generate manually curated annotation databases in biology <ref name=":0">{{Cite journal
 | pmid = 18834495
| year = 2008
| last1 = Krallinger
| first1 = M
| title = Overview of the protein-protein interaction annotation extraction task of Bio ''Creative'' II
| journal = Genome Biology
| volume = 9
| pages = S4
| last2 = Leitner
| first2 = F
| last3 = Rodriguez-Penagos
| first3 = C
| last4 = Valencia
| first4 = A
| issue = Suppl 2
| doi = 10.1186/gb-2008-9-s2-s4
| pmc = 2559988
| doi-access = free
}}</ref>