Song Recommendation Engine Tianlai Karaoke App Gao Wa, Cui - - PowerPoint PPT Presentation

Tianlai Karaoke App

Gao Wa, Cui Xiaoting, Zheng Feng Advisor: Professor Li Yanhua Technical support: Xu Hengyu (Tianlai)

Song Recommendation Engine

Tianlai Karaoke App

What is Tianlai?

• Your own karaoke platform
• Record your singing, and post your songs on

your channel to share with others

• Add friends and build your interest circle

Tianlai is popular

• Award for the best creative app and most popular music app
• 35 million TV installation & 0.4 billion mobile installation

Problem Statement

• How to increase target users engagement with the App?
• Build a good recommendation system
• Identify the factors that most affecting users song preference
• Find users’ features that are most useful for song recommendation
• Whether user would sing along on recommended songs?
• The accuracy of our recommended songs

Sample Data

• Total of 33,489,549 records of 95,109 users and 329,789 songs (2013-2018)
• 50 Features : User features + song features + singer features

Data

Data Preprocessing

• Missing Values
• Features selection
• Create new feature

Data Preprocessing

• Combining records

Total 5000 records 20 users 4 types of interactions 100 songs

Methodology

Engine

Data Source Training Data Data Preparater Prepared Data

Model 2

Algorithm 2 Algorithm 1 Algorithm 3

Model 1 Model 3 Recommendation

Recommending Process

Algorithms

1. Predictive Model a. XGBoost b. Random Forest c. SVR 2. Collaborative Filtering a. User-user based b. Item-item based

Collaborative Filtering

Collaborative Filtering

User- item matrix User-feature matrix

user id song id 1 2 3 1 14 19 23 2 36 89 49 User id Singer - male Singer - female Song - type 1 1 14 19 23 2 36 89 49

Results

Algorithm Root Mean Square Error Algorithm Root Mean Square Error Random Forest 51.46 User-user CF 26.85 XGBoost 49.93 Item-item CF 28.39 Support Vector Machine 51.68 User-user CF (user-feature matrix) 29.29

Results

XGBoost Random Forest

Future Work

• Optimize the accuracy of models
• Add new algorithms such as deep learning
• Deploy recommendation engine on Karaoke App

We are looking for students to join our team! You are welcome to join through independent study or volunteering work!