This study applies the Case-Based Reasoning (CBR) technique to develop a case repository-based leisure constraints inference system. This system is expected to predict the type of leisure constraints that visitors encounter and help leisure service providers in negotiation of the constraints and strategic marketing. Empirical findings suggest that the hit rate of the proposed system for visitors? leisure constraints reaches 54.83%.
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