I declare that this report entitled "User Preferences of Songs Using Preference Learning in Artificial Intelligence" is my own work, except as noted in the references. I would like to express my sincere thanks and appreciation to my superiors, Ts Soong Hoong Cheng, who gave me this great opportunity to participate in user song settings using the Preference Learning and Artificial Intelligence project. This is my first step towards establishing a career in AI and machine leaning.
The music recommendation system should provide an efficient way to manage songs and help their customers classify all songs based on genres, artists, age groups, locations and language by providing quality recommendations. Thus, a good quality music recommendation system will have a strong user base and create a booming market. This project will implement different algorithms to compare the results to find out which is the most effective algorithm suitable for a music recommendation system.
LIST OF TABLES
LIST OF ABBREVIATIONS
INTRODUCTION
Introduction
- Background information
- Learning Objective
- Project objective
- To define the best algorithm for the recommender system
- To find out the solution of automatic playlist continuation
- To find out the solution of cold start problem
- To separate the huge dataset to smaller subset
The learning objective of this project is to first learn about machine learning and its key concepts and various data mining techniques and algorithms. This project will apply all types of classification models such as Random Forest Classifier, Logistic Regression, Support Vector Machine, Naïve Bayes, Decision Tree Classifier and K Neighbors Classifier [6]. Smaller subset would be more effective for this project than lack of resources to run the experiments with larger data set.
This project aims to find the correlation and similarity between music taste and listening history. Furthermore, the system well-structured web-based system will be deployed in this project which is FYP2. Furthermore, the project scope will indicate how to present the project and indicate the contribution of this project in the last part of Chapter 1.
In addition, Chapter 5: System Deployment and Testing discusses the work product and provides a test plan for the system developed in this project. Finally, Chapter 6: Conclusion deals with the summary of this project, such as the research limit and future work.
LITERATURE REVIEW
- Music Recommender System CS365: Artificial Intelligence
LITERATURE REVIEW
The second line is calculating the sum of the listen_count of each song in the grouped_sum variable. The third line is to create a new column name called percentage and calculate the value by dividing the number of listen_heard by the sum of listen_count and multiplying by 100. Users can search for songs with the Browse function, as Spotify has a wide range of genres for occasions different. Another strength of Apple Music is that it has more libraries of music content compared to other music recommendation apps.
According to the article [8], Apple music has more than 60 million songs, users can find music from artists they have not yet discovered. Apple Music also makes exclusive deals with artists like Taylor Swift and Drake to release content early, benefiting expectant fans. 18 In addition, Apple Music has another powerful feature, which is that users can search for songs by lyrics only.
Now users can type the lyrics directly in the app's search bar, the system will match the songs to the users accordingly. Finally, Apple Music should provide its own voice assistance functionality to the app without Siri.
System Methodology/Approach
- Design Specifications
- Methodologies and General Work Procedures
The design phase is the fundamental process of understanding why the system needs to be built and creating an idea of how the project will go about building it. In the analysis phase, he will analyze the questions of who will use the system, what the system will do and where it will be used. In this phase, she will investigate all existing systems, identify opportunities for improvement and develop a concept for a new system.
The next phase is design, the design phase will decide how the system will work, the user interface, forms, reports, specific programs, database and file that will be needed. During this phase, the system is built and usually receives the most attention because for most systems it is the longest and most expensive single part of the development phase. The developer must ensure the maintenance of the system, must perform the maintenance activity and monitor the performance of the system to ensure that the system is always executable [9].
SYSTEM METHODOLOGY/APPROACH
- Tools to use Programming language
From web development to game development to machine learning, there's a library for almost anything you can think of. Python allows you to do more with less code, which means you can create prototypes and test concepts faster than with other languages.
Visual Studio Code
Hardware Involved
Software Involved
- User Requirements Functional Requirements
- System Performance Definition
- System Design/Overview .1 System Flowchart
- User Interface Design
- Use Case Diagram
- Use Case Description Register Account
- Activity Diagram Register Account
- Implementation Issues and Challenges
- Verification Plan
The performance of the system will be evaluated on the accuracy and prediction of the songs to the users.
Register Account
Login Account
Reset Password
Play Songs
Refresh Songs
Add to Favourite
Remove Favourite
Log Out
- Timeline .1 FYP 1
- FYP 2
Experiment and Model Implementation
- Experiment Conducted with Various Model
EXPERIMENT AND MODEL IMPLEMENTATION
- Model Implementation with Collaborative Filtering Method
The simple experiment shows that the classification models are not suitable for the recommendation system, because the results of actual versus predicted values from Figure 4.1.3 are very poor. After initialization, we need to calculate the similarity between the songs listened to by the user and all the unique songs in the training data. The variables i and j are used to calculate the intersection between the users and the numbers.
The function will average the scores in the co-occurrence matrix for all the tracks the user is listening to. Next, create and populate a data frame for user_id, song, score, and rank with the top 10 songs. Then get all the unique songs by user and get all the songs in the dataset.
From Figure 4.2.4 shows that the system will display songs played by the user with user_id.
SYSTEM IMPLEMENTATION AND TESTING
System Implementation and Testing 5.1 Project Screenshot and Explanation
- Login Fail
- Sign Up
- Reset Password
- Firebase
- Main Menu
- Play Song
- Refresh Song
- Add to Favourite
- Log Out
- Module Testing
- Account Login Testing Test
- Account Registration Testing Test Case
- Reset Password Testing Test
- Play Song Testing Test Case
- Refresh Song Testing Test Case
- Add to Favourite Testing Test Case
- Remove Favourite Testing Test Case
- Logout Testing Test Case
Following user input not under registered email or wrong password, system will prompt error message like “Invalid email”. On the login page, the system will ask the user to enter a username, password and email address. The system will ask the user to enter a password with at least 6 characters.
After entering the registered email address, the system will send a link to reset the password. After clicking the Play Song button, the system will automatically redirect the user to the corresponding YouTube video. When the user clicks the Favorites button, the system will add the track to the favorites list, which is shown in Figure 5.1.9.1.
When the user clicks the Log Out button, the system will redirect the user back to the login page.
CONCLUSION
CONCLUSION
2018, April) “Current Challenges and Visions in Music Recommendation Systems Research”, Int J Multimed Info Retr 7, [Online Introduction to Music Recommendation and Machine Learning”. Music Recommendation System Based on Genre Using Convolutional Recurrent Neural Networks.” Procedia Computer Science pp. 99-109 Educational: Interactive Courses for Software Developers.” [Online] Available: https://www.educative.io/edpresso/what-is-firebase.
Certificate of Presentation
FINAL YEAR PROJECT WEEKLY REPORT
WORK DONE
WORK TO BE DONE
PROBLEMS ENCOUNTERED N/A
SELF EVALUATION OF THE PROGRESS
PROBLEMS ENCOUNTERED
WORK TO BE DONE i. Writing report
SELF EVALUATION OF THE PROGRESS i. Work is on track
Poster
PLAGIARISM CHECK RESULT
Required originality parameters and limits approved by UTAR are as follows:. i) Overall similarity index is 20% and below, and. ii) Matching of individual cited sources must be less than 3% each, and (iii) Matching texts in consecutive block must not exceed 8 words. Note: Parameters (i) – (ii) must exclude citations, bibliography and text matches that are less than 8 words. Note Supervisor/candidate(s) are required to deliver a soft copy of the full set of the originality report to the faculty/department.
Based on the above results, I declare that I am satisfied with the authenticity of the Final Year Project Report submitted by my student(s) as mentioned above. Form title: Supervisor's Comments on Originality Report Generated by Turnitin for submission of Final Year Project Report (for Undergraduate Programs).
UNIVERSITI TUNKU ABDUL RAHMAN
