3-LAYER ARCHITECTURE FOR DETERMINING THE PERSONALITY TYPE FROM HANDWRITING ANALYSIS BY COMBINING NEURAL NETWORKS AND SUPPORT VECTOR MACHINES

We propose a 3-layer architecture for determining the personality type of a subject by only analyzing handwriting. The proposed architecture combines Neural Network and Support Vector Machine approaches and it is tested in various configurations for determining which combination offers the best pers...

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Bibliographic Details
Published inScientific Bulletin. Series C, Electrical Engineering and Computer Science no. 4; p. 135
Main Author Gavrilescu, Mihai
Format Journal Article
LanguageEnglish
Published Bucharest University Polytechnica of Bucharest 01.01.2017
Subjects
Handwriting analysis
Neural networks
Personality
Support vector machines
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Summary:We propose a 3-layer architecture for determining the personality type of a subject by only analyzing handwriting. The proposed architecture combines Neural Network and Support Vector Machine approaches and it is tested in various configurations for determining which combination offers the best personality type classification results for each mixture of handwriting features. In order to test the system, we created a new training database based on Myers-Briggs Type Indicator (MBTI) questionnaire with the purpose of eliminating the inconsistencies of the experimental results compared to manual analysis. We present the architecture, the experimental results, as well as further improvements that could be brought to the current architecture.
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ISSN:2286-3540