Automatic Classification of Cross-Domain Opinions

Authors

  • Rafael Guzman Cabrera Universidad de Guanajuato

DOI:

https://doi.org/10.13053/cys-23-4-3307

Keywords:

Opinion classification, machine learning, subjective

Abstract

It is increasingly common for internet users to have access to blogs and social networks. On these sites it is common to issue opinions. Opinions allow people to measure the perception of a particular topic or product. When the number of opinions is very large, its analysis becomes more complicated and it is generally sought to resort to tools that allow this task to be carried out automatically. In the present work the automatic categorization of text opinions is carried out. These opinions correspond to four products: books, DVDs, kitchens and electronics. You have both positive and negative opinions. Categorization results are presented using cross domains as training and testing, using different learning methods and are complemented with similarity graphs, which allow us to have a visual reference of the proximity of the language between the different domains under study. The results obtained allow us to see the feasibility of the proposed methodology.

Author Biography

Rafael Guzman Cabrera, Universidad de Guanajuato

Profesor Titular BDepartamento de Ingenieria Electrica

Downloads

Published

2019-12-20

Issue

Vol. 23 No. 4 (2019): 23-4(2019)

Section

Articles

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.