  This paper addresses a comprehensive pipeline to build a hotel recommendation
system with the raw data collected by Apps in users' smartphones. The pipeline
mainly consists of pre-processing of the raw data and training prediction
models. We use two methods, Support Vector Machine (SVM) and Recurrent Neural
Network (RNN). The results show that two methods achieved a reasonable accuracy
with the pre-processing of the raw data. Therefore, we conclude that this paper
provides a comprehensive pipeline, in which a hotel recommendation system was
successfully built from the raw data to specific applications.
