Implementation and effect evaluation of intelligent recommendation algorithms on hotel reservation platforms
智能推荐算法在酒店预定平台上的实现与效果评估

摘要

智能推荐算法在提升酒店预订平台用户体验和增加转化率方面扮演着关键角色。本研究旨在探讨不同类型智能推荐算法的实现方式及其对酒店预订平台性能的影响。通过对几种主流推荐算法进行实验评估，发现基于协同过滤的方法在提高用户满意度和个性化服务方面表现尤为突出。通过分析用户行为数据优化推荐策略，可以显著提升预订成功率。有效的推荐系统不仅能增强客户粘性，还能为酒店带来更高的收益。推荐系统的准确性和用户隐私保护仍是需要解决的重要问题。

Abstract

Intelligent recommendation algorithms play a crucial role in enhancing the user experience on hotel reservation platforms and increasing the conversion rate. This study aims to explore the implementation methods of different types of intelligent recommendation algorithms and their impacts on the performance of hotel reservation platforms. Through experimental evaluation of several mainstream recommendation algorithms, it is found that the collaborative filtering-based approach performs particularly prominently in improving user satisfaction and personalized services. By analyzing user behavior data to optimize the recommendation strategy, the reservation success rate can be significantly increased. An effective recommendation system can not only enhance customer stickiness but also bring higher revenues to hotels. The accuracy of the recommendation system and the protection of user privacy remain important issues that need to be addressed.