Title :
A Hotel Recommendation System Based on Collaborative Filtering and Rankboost Algorithm
Author :
Gao Huming ; Li Weili
Author_Institution :
Inf. Manage. Dept, Tianjin Univ. of Econ. & Finance, Tianjin, China
Abstract :
A hotel recommendation system based on collaborative filtering method of clustering and Rankboost algorithm proposed in this paper, which can avoid the cold-start and scalability problems existing in traditional collaborative filtering. One can find a hotel quickly and efficiently when he uses this hotel recommendation system.
Keywords :
Internet; hotel industry; recommender systems; collaborative filtering method; hotel recommendation system; rankboost algorithm; Clustering algorithms; Filtering algorithms; Finance; Information filtering; Information filters; Information management; Information technology; International collaboration; Multimedia systems; Scalability;
Conference_Titel :
Multimedia and Information Technology (MMIT), 2010 Second International Conference on
Conference_Location :
Kaifeng
Print_ISBN :
978-0-7695-4008-5
Electronic_ISBN :
978-1-4244-6602-3
DOI :
10.1109/MMIT.2010.14
