Customized Opinion Mining using Intelligent Algorithms

  • Pablo Cababie
  • Alvaro Zweig
  • Gabriel Barrera
  • Daniela Lopéz De Luise
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 151)

Abstract

Since the INTERNET outburst, consumer perception turned into a complex issue to be measured. Non-traditional advertising methods and new product exhibition alternatives emerged. Forums and review sites allow end users to suggest, recommend or rate products according to their experiences. This gave raise to the study of such data collections. After analyze, store and process them properly, they are used to make reports used to assist in middle to high staff decision making. This research aims to implement concepts and approaches of artificial intelligence to this area. The framework proposed here (named GDARIM), is able to be parameterized and handled to other similar problems in different fields. To do that it first performs deep problem analysis to determine the specific domain variables and attributes. Then, it implements specific functionality for the current data collection and available storage. Next, data is analyzed and processed, using Genetic Algorithms to retro feed the keywords initially loaded. Finally, properly reports of the results are displayed to stakeholders.

Keywords

Opinion mining Crawling Genetic algorithms 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Pablo Cababie
    • 1
  • Alvaro Zweig
    • 1
  • Gabriel Barrera
    • 1
  • Daniela Lopéz De Luise
    • 1
  1. 1.Univesidad de PalermoBuenos AiresArgentina

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