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A content based movie recommender system for mobile application

Final Year Project Phase 1 Presentation Slide

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A content based movie recommender system for mobile application

  1. 1. A Content-based MovieRecommender System for Mobile Application Supervisor: Dr. Khairil Imran Gauth Moderator: Dr. Yeoh Eng Thiam Presenter: Ahmad Arafat Bin Mohd Ali (1091105499)
  2. 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. 3. Problem DescriptionPeople have problem in selecting alternative items(eg. movies)Get movie recommended by friends or movie expertreviews from website / magazine- > Time consumingNeed large data set of movie collectionMobile Phones in the market has limited processingpower to handle the recommender systemcalculation. Solution - > Web Services
  4. 4. Project ObjectivesDevelop an algorithm for recommending moviesWorking with a large dataset of movies (sourceGroupLens)Implement Web-Services (server-side) -Advantage: Increase performance in the mobile phoneImplement Mobile Application (client-side)
  5. 5. Background Study & Literature ReviewThe Internet Movie Database (IMDb) Features: -Auto Movie Recommendation -Watch List -Like Feature Weakness: -Lack of Sign in Feature -Inaccurate Movie Ranking
  6. 6. Background Study & Literature ReviewFlixster Feature: -Movie Rating Monitoring -Film Quizzes and Games -Video and Picture Sharing Weakness: Rating System is not monitored
  7. 7. Background Study & Literature ReviewNetFlix Feature: -Excellent Content Availability -Platform Varsity Weakness: -Content Coverage is limited
  8. 8. Background Study & Literature ReviewMSN 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. 9. Finding of Questionnaire50 Respondents-32 Males-18 Females Majority of the respondents watch movie weekly
  10. 10. Finding of QuestionnaireMajority of the respondents have mobile phone with internetaccess
  11. 11. Finding of QuestionnaireMajority of the respondents wanted to have a movierecommender system on their mobile phone
  12. 12. Finding of QuestionnaireSome of the features wanted to be seen in the movierecommender system
  13. 13. Proposed Solution AlgorithmUse Overlap Coefficient algorithm to make movierecommendation
  14. 14. Proposed Solution Use Case Diagram
  15. 15. Proposed Solution Entity Relationship Diagram
  16. 16. System Interface 1 Search Function
  17. 17. System Interface 2 Movie Description
  18. 18. System Interface 3 Main page after user has logged in
  19. 19. Q&A