DocumentCode :
2895326
Title :
Improving text categorization: A fully automated ontology based approach
Author :
Machhour, Hamid ; Kassou, Ismail
Author_Institution :
ENSIAS, Mohammed V Souissi Univ., Rabat, Morocco
fYear :
2013
fDate :
19-21 June 2013
Firstpage :
67
Lastpage :
72
Abstract :
This paper presents an improvement of text categorization models by document annotation with previously imported ontologies. A fully automated algorithm will be introduced to annotate plain text documents. Simple strategies combining annotation results with the categorization models are also presented and experienced. Conducted experiments present an improvement of tested categorization models when mixed with the annotation results.
Keywords :
ontologies (artificial intelligence); text analysis; automated algorithm; categorization models; document annotation; ontology; plain text documents; text categorization; Dictionaries; Niobium; Ontologies; Telecommunications; Text categorization; Vectors; Text categorization; domain ontology; text annotation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications and Information Technology (ICCIT), 2013 Third International Conference on
Conference_Location :
Beirut
Print_ISBN :
978-1-4673-5306-9
Type :
conf
DOI :
10.1109/ICCITechnology.2013.6579524
Filename :
6579524
Link To Document :
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