One of the major challenges hotel businesses face today lies in the complex process of figuring out or predicting their customers’ preferences. With more options for guests and higher standards, hotels tend to personalize the experiences based on specific preferences. Yet, this is a complicated task due to the changing tastes of guests and their varied nature. Traditional techniques are usually unable to catch the subtle details of guests’ needs, which results in the loss of chance for personalization and customer satisfaction rate. The models typically rely on a single algorithm or model to make predictions, which may lead to limited accuracy and generalization, especially in complex and dy
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