论文标题
使用机器学习的餐厅推荐研究
Research on restaurant recommendation using machine learning
论文作者
论文摘要
推荐系统是一个系统，可帮助用户根据其历史记录过滤无关的信息并创建用户兴趣模型。随着互联网信息的持续开发，推荐系统在行业中受到了广泛关注。在这个无处不在的数据和信息时代，如何获得和分析这些数据已成为许多人的研究主题。鉴于这种情况，本文简要概述了与机器学习相关的推荐系统。通过分析推荐系统中机器学习使用的一些技术和想法，让更多的人了解什么是大数据以及什么是机器学习。最重要的是让每个人都了解机器学习对我们日常生活的深远影响。
A recommender system is a system that helps users filter irrelevant information and create user interest models based on their historical records. With the continuous development of Internet information, recommendation systems have received widespread attention in the industry. In this era of ubiquitous data and information, how to obtain and analyze these data has become the research topic of many people. In view of this situation, this paper makes some brief overviews of machine learning-related recommendation systems. By analyzing some technologies and ideas used by machine learning in recommender systems, let more people understand what is Big data and what is machine learning. The most important point is to let everyone understand the profound impact of machine learning on our daily life.
