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Web-based Movie Recommender System Using User Preference Models with Adjusted Euclidean Distance Similarity Measure

Acknowledgements第4-5页
abstract第5页
Abbreviations第8-12页
CHAPTER 1: INTRODUCTION第12-16页
    1.1 Background第12-13页
    1.2 Purpose第13页
    1.3 Approach第13-15页
    1.4 Thesis Structure第15-16页
CHAPTER 2: RECOMMENDATION SYSTEMS AND RELATED WORK第16-33页
    2.1 Information retrieval and filtering第16-18页
    2.2 Recommendation Systems第18-25页
    2.3 Common Drawbacks in Recommender Systems第25-27页
    2.4 Related work第27-33页
CHAPTER 3: PROPOSED SIMILARITY MEASURES第33-57页
    3.1 Collaborative filtering Approach第33-34页
    3.2 The Modeling of Approach第34页
    3.3 AED similarity measure based on user preference models第34-39页
    3.4 Experiments and Evaluation第39-51页
    3.5 Challenges for Application Development第51-57页
CHAPTER 4: APPLICATION DEVELOPMENT第57-73页
    4.1 Existing Online Movie Recommendation Systems第57-58页
    4.2 System Overview第58-59页
    4.3 Choice of Programming Language and Web Framework第59-61页
    4.4 Functional Requirements of Application第61-66页
    4.5 Non-Functional Requirements第66-67页
    4.6 System Requirements第67-69页
    4.7 Use case Diagrams第69-73页
CHAPTER 5: APPLICATION DESIGN第73-87页
    5.1 Application Components第73-74页
    5.2 Flow Chart Diagrams第74-81页
    5.3 Database第81-87页
CHAPTER 6: IMPLEMENTATION AND TESTING OF APPLICATION第87-107页
    6.1 Implementation Environment第87-88页
    6.2 Django Project File Structure第88-89页
    6.3 Django Project Components第89-95页
    6.4 Frontend Interface第95-102页
    6.5 Admin Interface第102页
    6.6 Testing of Application第102-107页
CHAPTER 7: CONCLUSION AND FUTURE WORK第107-109页
    7.1 Conclusion第107页
    7.2 Future Work第107-109页
REFERENCES第109-112页

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