A Hotel Recommendation System Based on Collaborative Filtering and Rankboost Algorithm

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.

[1]  Wang Ting-zhong.  Collaborative filtering recommendation based on user clustering in personalization service , 2007 .

[2]  Yoram Singer,et al.  An Efficient Boosting Algorithm for Combining Preferences by , 2013 .

[3]  Fuyuki Ishikawa,et al.  Improving Accuracy of Recommender System by Clustering Items Based on Stability of User Similarity , 2006, 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06).

[4]  Songjie Gong.  A Collaborative Filtering Recommendation Algorithm Based on User Clustering and Item Clustering , 2010, J. Softw..