Choosing an appropriate gift is difficult because the purpose of gift giving is to arouse affection in the receiver, not the giver, and too many variables that influence the results. Utilizing 600 samples and a hybrid method combining the decision tree and K-nearest neighbor approaches, this study builds a DTKNN two-stepped recommendation system which achieves a precision rate higher than 80%. The contribution of this research is to propose a new data mining technique to solve the problem of a recommendation system for altruistic gift selection which allows the receiver to perceive the affection desired by the giver. K EY W ORDS:Recommendation system, Gift giving, Decision tree, K-nearest neighbor.
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