论文标题
酒店推荐系统的全面管道
A Comprehensive Pipeline for Hotel Recommendation System
论文作者
论文摘要
本文介绍了一条全面的管道，该管道通过用户智能手机中的应用程序收集的原始数据来建立酒店推荐系统。该管道主要包括对原始数据和培训预测模型的预处理。我们使用两种方法：支持向量机（SVM）和复发性神经网络（RNN）。结果表明，通过预先处理原始数据，两种方法达到了合理的精度。因此，我们得出的结论是，本文提供了一条全面的管道，其中从原始数据到特定应用程序成功构建了酒店推荐系统。
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.
