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arXiv · 2009.01860

A Comprehensive Pipeline for Hotel Recommendation System

J. Chen·Z. Gao
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Abstract

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.

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J. Chen, Z. Gao. 2020-08-13. A Comprehensive Pipeline for Hotel Recommendation System. https://arxiv.org/abs/2009.01860

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