Research on restaurant recommendation using machine learning

TL;DR

This paper provides an overview of how machine learning techniques are applied in restaurant recommendation systems, emphasizing their role in handling big data and influencing daily life.

Contribution

It offers a brief overview of machine learning-based recommendation systems and discusses their technologies, ideas, and impact on data analysis and daily life.

Findings

Machine learning enhances recommendation accuracy.

Big data is crucial for effective recommendations.

Machine learning significantly impacts daily life.

Abstract

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.