  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.
