Switching between different ways to think: Multiple approaches to affective common sense reasoning

Cambria, Erik; Mazzocco, Thomas; Hussain, Amir; Durrani, Tariq

Abstract

Emotions are different Ways to Think that our mind triggers to deal with different situations we face in our lives. Our ability to reason and make decisions, in fact, is strictly dependent on both our common sense knowledge about the world and our inner emotional states. This capability, which we call affective common sense reasoning, is a fundamental component in human experience, cognition, perception, learning and communication. For this reason, we cannot prescind from emotions in the development of intelligent user interfaces: if we want computers to be really intelligent, not just have the veneer of intelligence, we need to give them the ability to recognize, understand and express emotions. In this work, we argue how graph mining, multi-dimensionality reduction, clustering and space transformation techniques can be used on an affective common sense knowledge base to emulate the process of switching between different perspectives and finding novel ways to look at things.

Citation

Cambria, E., Mazzocco, T., Hussain, A., & Durrani, T. (2010, September). Switching between different ways to think: Multiple approaches to affective common sense reasoning. Presented at COST 2102 International Conference, Budapest, Hungary

• Presentation Conference Type: Conference Paper (published)
• Conference Name: COST 2102 International Conference
• Start Date: Sep 7, 2010
• End Date: Sep 10, 2010
• Publication Date: 2011
• Deposit Date: Oct 15, 2019
• Publisher: Springer
• Pages: 56-69
• Series Title: Lecture Notes in Computer Science
• Series Number: 6800
• Series ISSN: 0302-9743
• Book Title: Analysis of Verbal and Nonverbal Communication and Enactment. The Processing Issues: COST 2102 International Conference, Budapest, Hungary, September 7-10, 2010, Revised Selected Papers
• ISBN: 978-3-642-25774-2
• DOI: https://doi.org/10.1007/978-3-642-25775-9_5
• Keywords: Sentic Computing; AI; Semantic Web; NLP; Cognitive and Affective Modeling; Opinion Mining and Sentiment Analysis
• Public URL: http://researchrepository.napier.ac.uk/Output/1793401