title: Discrete classification technique applied to TV advertisements liking recognition system based on low-cost EEG headsets.
abstract: BACKGROUND
  In this paper a new approach is applied to the area of marketing research. The aim of this paper is to recognize how brain activity responds during the visualization of short video advertisements using discrete classification techniques. By means of low cost electroencephalography devices (EEG), the activation level of some brain regions have been studied while the ads are shown to users. We may wonder about how useful is the use of neuroscience knowledge in marketing, or what could provide neuroscience to marketing sector, or why this approach can improve the accuracy and the final user acceptance compared to other works.
  
  
  METHODS
  By using discrete techniques over EEG frequency bands of a generated dataset, C4.5, ANN and the new recognition system based on Ameva, a discretization algorithm, is applied to obtain the score given by subjects to each TV ad.
  
  
  RESULTS
  The proposed technique allows to reach more than 75 % of accuracy, which is an excellent result taking into account the typology of EEG sensors used in this work. Furthermore, the time consumption of the algorithm proposed is reduced up to 30 % compared to other techniques presented in this paper.
  
  
  CONCLUSIONS
  This bring about a battery lifetime improvement on the devices where the algorithm is running, extending the experience in the ubiquitous context where the new approach has been tested.
authors.affiliation: Computer Languages and Systems Dept, University of Seville, Avda. Reina Mercedes s/n, 41012, Seville, Spain. lsoria@us.es.
authors.forename: Luis M
authors.initials: LM
authors.lastname: Soria Morillo
authors.affiliation: Computer Languages and Systems Dept, University of Seville, Avda. Reina Mercedes s/n, 41012, Seville, Spain.
authors.forename: Juan A
authors.initials: JA
authors.lastname: Alvarez-Garcia
authors.affiliation: Applied Economics I Dept, University of Seville, Avda. Ramon y Cajal, 1, 41018, Seville, Spain.
authors.forename: Luis
authors.initials: L
authors.lastname: Gonzalez-Abril
authors.affiliation: Computer Languages and Systems Dept, University of Seville, Avda. Reina Mercedes s/n, 41012, Seville, Spain.
authors.forename: Juan A
authors.initials: JA
authors.lastname: Ortega Ramírez
mesh_terms: D000328:Adult; D000329:Advertising; D001921:Brain / Q000502:physiology*; D003663:Decision Trees; D004569:Electroencephalography / Q000191:economics* / Q000295:instrumentation*; D004644:Emotions; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D012815:Signal Processing, Computer-Assisted
keywords: Advertising; Brain-computer interaction; EEG; Electroencephalography; Neuromarketing