Title :
Text categorization using copula function: An overview
Author :
Hammami, N. ; Goudjil, Mohamed ; Alruily, Meshrif
Author_Institution :
Fac. of Comput. Sci. & Inf., Al Jouf Univ., Sakaka, Saudi Arabia
Abstract :
In this paper, we investigate a new joint statistical model for text classification, which is copula functions, that is a way of formalizing dependence structures of random vectors. A copula is a distribution function with the implicit capacity to model nonlinear dependencies. Copula have been widely used in economics and finance and more recently it has been used in same field of pattern recognition.
Keywords :
statistical distributions; text analysis; vectors; copula function; dependence structure formalization; distribution function; nonlinear dependency modelling; random vectors; statistical model; text categorization; text classification; Distribution functions; Joints; Probabilistic logic; Random variables; Standards; Support vector machine classification; Text categorization; Automatic Text Classification; Copula; Copula Function; Probabilistic Classification; Text categorization;
Conference_Titel :
Computer and Information Technology (WCCIT), 2013 World Congress on
Conference_Location :
Sousse
Print_ISBN :
978-1-4799-0460-0
DOI :
10.1109/WCCIT.2013.6618781
