Design and Implementation of Pet Recommendation System based on Machine Learning

This project will be based on JAVA development language, rely on Vue, Spring-Boot and other frameworks, and adopt machine learning recommendation algorithm to build a pet intelligent recommendation system, according to the user's life habits to help users solve the problem of pet selection. This project first collected 1056 pet behavior data on the Python requests network. At the same time, the data cleaning, coding and other pre-processing operations. Secondly, feature indexes are extracted from the original data, and then cluster analysis is conducted based on the k-means clustering algorithm based on the feature values. The original pet data is divided into five categories and the characteristics of the five categories are analyzed, and appropriate recommendations are given to users according to their living habits and characteristics.