@article {Rocha2015,
	title = {Semantic Annotation and Classification in Practice},
	journal = {IT Professional},
	volume = {17},
	year = {2015},
	month = {3},
	pages = {33-39},
	abstract = {<p>\&copy; 2015 IEEE. The Web\&$\#$39;s evolution into a Semantic Web and the continuous increase in the amount of data published as linked data open up new opportunities for annotation and categorization systems to reuse these data as semantic knowledge bases. Accordingly, information extraction systems use linked data to exploit semantic knowledge bases, which can be interconnected and structured to increase the precision and recall of annotation and categorization mechanisms. TellMeFirst classifies and enriches textual documents written in English and Italian. Although various works present solutions for text annotation and classification, this article describes and studies the use case of a telecommunications operator that has adopted TellMeFirst to add value to two services available to its users: FriendTV and Society.</p>
},
	keywords = {information extraction, linked data, semantic annotation, semantic classification},
	issn = {1520-9202},
	doi = {10.1109/MITP.2015.29},
	url = {http://ieeexplore.ieee.org/document/7077255/},
	author = {Oscar Rodriguez-Rocha and Iacopo Vagliano and Cristhian Figueroa and Federico Cairo and Giuseppe Futia and Carlo Alberto Licciardi and Marco Marengo and Federico Morando and Christian Nicol{\'a}s Figueroa Mart{\'\i}nez}
}
