A Hotel Recommendation Method based on Hotel Feature Analysis using Surrounding Facilities
Teng Li, Yuanyuan Wang · 2022 Joint 12th International Conference on Soft Computing and Intelligent Systems and 23rd International Symposium on Advanced Intelligent Systems (SCIS&ISIS) · 2022
In this paper, we propose a method for recommending hotels to users’ destinations by analyzing the features of the hotels, such as RATING, VALUE, COST, and ATTRIBUTE, from facilities surrounding the hotels for supporting hotel selection. We then calculate the scores for four different attributes: shopping, eating, entertainment, and service, based on each hotel’s features, and recommend the hotels to the users based on the hotels’ scores according to their needs. Finally, we verified the relevance between hotel attributes using Spearman’s rank correlation coefficient, and we discussed our proposed recommendation method using the NDCG to measure the accuracy of the proposed hotel rankings. As a result, we confirmed that the area types, scales, and locations could affect the correlation between hotel attributes; and the scales and locations could affect the accuracy of our proposed method.