Abstract
Starting with currently available data sets that capture the relationships between different pairs of personality-related constructs (for instance, descriptions of behaviors and personality traits), we describe a way of representing personality traits, human values, beliefs, and behaviors in one integrated network-centric model. We propose that such a unified representation can contribute to the making of predictions from one type of construct to another, for example, between personality characteristics and value preferences. Using a spreading activation mechanism, we show how, in principle, such a model can be used to make inferences about the plausibility of unobserved characteristics of an individual, given a very limited initial set of known characteristics.
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Quek, BK., Sakamoto, K., Ortony, A. (2009). A Data-Fusion Approach to Representing Personality Traits, Values, Beliefs and Behavior Descriptions. In: Lopes, L.S., Lau, N., Mariano, P., Rocha, L.M. (eds) Progress in Artificial Intelligence. EPIA 2009. Lecture Notes in Computer Science(), vol 5816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04686-5_14
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DOI: https://doi.org/10.1007/978-3-642-04686-5_14
Publisher Name: Springer, Berlin, Heidelberg
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