Basic Soft Computing Methods In User Profile Modeling
Petya Petrova ()
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Petya Petrova: University of Economics â€“ Varna/Department of Informatics, Bulgaria
Conferences of the department Informatics, 2019, issue 1, 353-368
User profile modeling is a challenge because of the high degree of subjectivity and uncertainty of human behavior. The traditional methods used to create user profile models do not have the necessary flexibility to capture the inherent uncertainty. The purpose of this research is to present adequate methods for modeling a user profile in their role as a learner. The soft computing methods - neural networks, fuzzy logic, fuzzy clustering, neuro-fuzzy approaches and genetic algorithms â€“ applied individually or in combination with other machine learning methods could be used for this purpose, due to the appropriate specific-ity of each one of them. The results of a research on the suitability of the basic soft computing methods for modeling a learnerâ€™s profile are presented in this paper.
Keywords: Soft computing; User profile modeling; Learner profile model; Student profile model (search for similar items in EconPapers)
JEL-codes: C8 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:vrn:katinf:y:2019:i:1:p:353-368
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