DocumentCode :
456456
Title :
A Bayesian Approach for Text Classification
Author :
Colace, Francesco ; De Santo, Massimo
Author_Institution :
DIIIE, Universitd di Salerno, Fisciano
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
1323
Lastpage :
1326
Abstract :
The continuous increase of digital information requires technologies and techniques that can easily and quickly manage them. One of the most important and hot topic in this field is the introduction of techniques for text classification. The aim of this paper is the design and the implementation of a method for text classification. In particular we used an approach based on the use of Bayesian networks. In order to test our approach we use it on the standard Reuters database. The obtained results are very promising
Keywords :
belief networks; classification; text analysis; Bayesian network; Reuters database; text classification; Bayesian methods; Databases; Expert systems; Machine assisted indexing; Probability distribution; Random variables; Technology management; Testing; Text categorization; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Communication Technologies, 2006. ICTTA '06. 2nd
Conference_Location :
Damascus
Print_ISBN :
0-7803-9521-2
Type :
conf
DOI :
10.1109/ICTTA.2006.1684572
Filename :
1684572
Link To Document :
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