Practical Application of Knowledge Graph 21 - Recommendation System for Chinese Music Based on Py2neo's Knowledge Graph

Hello everyone, I am Weixue AI. Today, I will introduce to you the practical application of knowledge graph 21-Chinese music recommendation system based on Py2neo's knowledge graph. This article will build a knowledge graph of Chinese music. This process includes collecting Chinese music related information. Data, such as songs, artists, albums, etc., and model these information as entities and attributes in the knowledge graph. You can use the Py2neo library to connect to the graph database and write code to import data into the knowledge graph.

Next, use the information in the knowledge graph for music recommendation. First of all, we can make personalized recommendations based on the user's historical listening records and preferences. By analyzing information such as songs, artists, and albums that users have already listened to, we can find similar musical entities and recommend them to users. This can be achieved by leveraging relational and attribute information in a graph database, such as finding songs similar to a user's favorite song, or other songs by the same artist.

In addition, more information in the knowledge graph can also be leveraged to provide a richer recommendation experience. For example, we can make recommendations based on genre, recommending songs for users that match their preferred music genres. We can use the song genre attributes in the knowledge graph to find songs that match the user's favorite genre and add them to the recommendation list.

Table of contents

1. introduction
2. Background of the project
3. Introduction to Py2neo
4. Introduction to Neo4j Graph Database
5. data preparation
6. Build knowledge graph
7. Music Recommendation System
8. in conclusion

1 Introduction

With the rapid development of information society, people's demand for music recommendation system is also increasing. The music recommendation system can provide users with personalized music recommendations according to the user's personal preferences and music characteristics, which greatly facilitates the user's music exploration and enjoyment.

This article will introduce a Py2neo-based knowledge graph combined with a Chinese music recommendation system implementation method. A knowledge graph is a graph database for storing and representing domain knowledge, which can connect entities, relationships and attributes to each otherÿ