Temperament-Based Information Filtering: A Human Factors Approach to Information Recommendation
نویسندگان
چکیده
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.
منابع مشابه
Exploiting and Learning Human Temperaments for Customized Information Recommendation
Human temperaments have been recognized as a predominant factor in determining the activity patterns of human behavior. In our earlier study, temperament-based filtering method has been proposed in seek of combining concept learning and content-based filtering techniques to incorporate human temperament concept into the recommendation process of an information system. In this paper, we explain ...
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