PROBABILISTIC INTENTION CLASSIFICATION FOR HUMAN AUGMENTED COGNITION SYSTEM

• Abstract:

  In this paper, we present a probabilistic human implicit intention classification using user’s eye gaze data for human augmented cognition system. The Ultimate purpose of this method is to implement a human augmented cognition system which can provide a specific service to address the cognitive limitations of human brain. In order to partially overcome the cognitive limitations, the system should be able to control the flow of information. Therefore, a specific intention classification using a Naïve Bayes classifier can be used as useful tool for searching and retrieving specific information according to the human intention and situation.
• Keywords:

  human intention, Naïve Bayes, human augmented cognition, system architecture
• Download:

  IMEKO-WC-2012-TC18-P4.pdf
• DOI:

  _unreg_wc-2012.TC18-P4

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