Yuan Zhang, Shiqi Liu
Shenzhen Campus, Jinan University, Shenzhen, 518052, China
Due to the subjective nature of the experience, it is challenging to classify travel products according to uniform criteria as physical products, which poses a significant challenge for recommendation techniques. In practical application scenarios, this study introduces an alternative image-based approach as an implicit elicitation of user preferences for travel products to accurately recommend products to travellers with different tastes. We developed a model based on exploratory factor analysis. First, based on exploratory factor analysis, we compared the pictures tapped by users to five types of travel preferences. Then, we use the Euclidean algorithm to project the images and scenic spot features into a five-dimensional space. It calculates the distance, thus quantifying the relationship between the travel and the user's favourite pictures. The final result shows that the model effectively improves the user's travel matching and effectively contributes to the field of travel destination recommendation.
Travel recommendation algorithm, Travel personality, Factor analysis
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