Abstract
Our lives are rewritten by technology and data, making it crucial for machines to understand humans and their behavior and react accordingly. Technology systems could adapt to different factors such as affect (Affective Computing), personality (Personality Computing), or character (Character Computing). Character consists of personality, affect, socio-cultural embedding, cognitive abilities, health, and all other attributes distinguishing one individual from another. Ontology-based conceptual models representing individuals i.e. their character and resulting behavior in situations is needed for providing a unified framework for building truly interactive and adaptive systems. We propose CCOnto, an ontology for Character Computing that models human character. The ontology is to be used for adaptive interactive systems to understand and predict an individual’s behavior in a given situation, more specifically their performance in different tasks. The developed ontology models the different character attributes, their building blocks, and interactions with each other and with a person’s performance in different tasks.
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El Bolock, A., Herbert, C., Abdennadher, S. (2020). CCOnto: Towards an Ontology-Based Model for Character Computing. In: Dalpiaz, F., Zdravkovic, J., Loucopoulos, P. (eds) Research Challenges in Information Science. RCIS 2020. Lecture Notes in Business Information Processing, vol 385. Springer, Cham. https://doi.org/10.1007/978-3-030-50316-1_34
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DOI: https://doi.org/10.1007/978-3-030-50316-1_34
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