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2000
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Temperament-Based Information Filtering: A Human Factors Approach to Information Recommendation

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Temperament-Based Information Filtering: A Human Factors Approach to Information Recommendation
This paper provides an intelligent multiagent approach to incorporate human temperaments into the filtering process of an information recommendation service. Our approach is to devise a new filtering mechanism, which addresses segmentation, learning, classification, and filtering techniques based on Keirsey’s temperament theory, probability theory, the distributions of temperaments, and statistical reasoning. By presenting information units that are consistent with user interests as well as user temperament, the accuracy and precision of the recommendation service may be improved.
Cha-Hwa Lin, Dennis McLeod
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Where ICMCS
Authors Cha-Hwa Lin, Dennis McLeod
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