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A content based movie recommender system for mobile application

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Arafat X
Arafat X

Final Year Project Phase 1 Presentation Slide

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A Content-based Movie Recommender System for Mobile Application Supervisor: Dr. Khairil Imran Gauth Moderator: Dr. Yeoh Eng Thiam Presenter: Ahmad Arafat Bin Mohd Ali (1091105499)
Project Overview: - What is a Recommender System? -> Information Filtering System - Act as an information filtering from a large collection items (such as movies) by recommending some movies to users. - Develop a movie recommender system on a mobile phone
Problem Description People have problem in selecting alternative items (eg. movies) Get movie recommended by friends or movie expert reviews from website / magazine- > Time consuming Need large data set of movie collection Mobile Phones in the market has limited processing power to handle the recommender system calculation. Solution - > Web Services
Project Objectives Develop an algorithm for recommending movies Working with a large dataset of movies (source GroupLens) Implement Web-Services (server-side) -Advantage: Increase performance in the mobile phone Implement Mobile Application (client-side)
Background Study & Literature Review The Internet Movie Database (IMDb) Features: -Auto Movie Recommendation -Watch List -Like Feature Weakness: -Lack of Sign in Feature -Inaccurate Movie Ranking
Background Study & Literature Review Flixster Feature: -Movie Rating Monitoring -Film Quizzes and Games -Video and Picture Sharing Weakness: Rating System is not monitored
Background Study & Literature Review NetFlix Feature: -Excellent Content Availability -Platform Varsity Weakness: -Content Coverage is limited
Background Study & Literature Review MSN Movie Feature: -Movie Can be shared via Facebook -Find Movie Listing using third party search engine Weakness: - Smaller collection of movies - No rating and review features
Finding of Questionnaire 50 Respondents -32 Males -18 Females Majority of the respondents watch movie weekly
Finding of Questionnaire Majority of the respondents have mobile phone with internet access
Finding of Questionnaire Majority of the respondents wanted to have a movie recommender system on their mobile phone
Finding of Questionnaire Some of the features wanted to be seen in the movie recommender system
Proposed Solution Algorithm Use Overlap Coefficient algorithm to make movie recommendation
Proposed Solution Use Case Diagram
Proposed Solution Entity Relationship Diagram
System Interface 1 Search Function
System Interface 2 Movie Description
System Interface 3 Main page after user has logged in
Q&A

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A content based movie recommender system for mobile application

  • 1. A Content-based Movie Recommender System for Mobile Application Supervisor: Dr. Khairil Imran Gauth Moderator: Dr. Yeoh Eng Thiam Presenter: Ahmad Arafat Bin Mohd Ali (1091105499)
  • 2. Project Overview: - What is a Recommender System? -> Information Filtering System - Act as an information filtering from a large collection items (such as movies) by recommending some movies to users. - Develop a movie recommender system on a mobile phone
  • 3. Problem Description People have problem in selecting alternative items (eg. movies) Get movie recommended by friends or movie expert reviews from website / magazine- > Time consuming Need large data set of movie collection Mobile Phones in the market has limited processing power to handle the recommender system calculation. Solution - > Web Services
  • 4. Project Objectives Develop an algorithm for recommending movies Working with a large dataset of movies (source GroupLens) Implement Web-Services (server-side) -Advantage: Increase performance in the mobile phone Implement Mobile Application (client-side)
  • 5. Background Study & Literature Review The Internet Movie Database (IMDb) Features: -Auto Movie Recommendation -Watch List -Like Feature Weakness: -Lack of Sign in Feature -Inaccurate Movie Ranking
  • 6. Background Study & Literature Review Flixster Feature: -Movie Rating Monitoring -Film Quizzes and Games -Video and Picture Sharing Weakness: Rating System is not monitored
  • 7. Background Study & Literature Review NetFlix Feature: -Excellent Content Availability -Platform Varsity Weakness: -Content Coverage is limited
  • 8. Background Study & Literature Review MSN Movie Feature: -Movie Can be shared via Facebook -Find Movie Listing using third party search engine Weakness: - Smaller collection of movies - No rating and review features
  • 9. Finding of Questionnaire 50 Respondents -32 Males -18 Females Majority of the respondents watch movie weekly
  • 10. Finding of Questionnaire Majority of the respondents have mobile phone with internet access
  • 11. Finding of Questionnaire Majority of the respondents wanted to have a movie recommender system on their mobile phone
  • 12. Finding of Questionnaire Some of the features wanted to be seen in the movie recommender system
  • 13. Proposed Solution Algorithm Use Overlap Coefficient algorithm to make movie recommendation
  • 14. Proposed Solution Use Case Diagram
  • 15. Proposed Solution Entity Relationship Diagram
  • 16. System Interface 1 Search Function
  • 17. System Interface 2 Movie Description
  • 18. System Interface 3 Main page after user has logged in
  • 19. Q&A