Research on Hotel Recommendation Systems Based on AHP and Collaborative Filtering Combination Algorithm
Chuanlin Huang, Yanqing Cui, Guojun Sheng · 2019
The Internet brings a lot of information to people. While satisfying people's demand for information, it also brings the problem of information overload. Recommendation systems show great potential in solving information overload and personalized needs. This paper studies the recommendation system and hotel recommendation problem for the specific recommendation object of the hotel. By analyzing the current situation and difficult problems of hotel recommendation, this paper proposes a hotel recommendation method combining AHP analytic hierarchy process and collaborative filtering algorithm. This method can quantify the weight of the main factors affecting customer selection, and predict the degree of preference of another customer for a hotel through the rating of similar customer groups, so as to select hotels that are more in line with customer preferences for recommendation.