2013/11/29 by Xudong Liu, Liu, Xudong, Bing Xu +14
Business, Management and Accounting · Computer Science · #Consumer Market Behavior and Pricing #Data Management and Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Recommender Systems and Techniques #cs.LG
paper · pdf · doi:10.48550/arxiv.1311.7679
6 pages, 3 figures
arxiv created 2013/11/29 · openalex publication_date 2013/11/29 · arxiv updated 2013/12/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The ICDM Challenge 2013 is to apply machine learning to the problem of hotel ranking, aiming to maximize purchases according to given hotel characteristics, location attractiveness of hotels, user's aggregated purchase history and competitive online travel agency information for each potential hotel choice. This paper describes the solution of team "binghsu & MLRush & BrickMover". We conduct simple feature engineering work and train different models by each individual team member. Afterwards, we use listwise ensemble method to combine each model's output. Besides describing effective model and features, we will discuss about the lessons we learned while using deep learning in this competition.