1. Introduction 2. Theoretical Foundations of Machine Learning 3. Theoretical Foundations of Personalized Recommendation Algorithms 4. A Frequent Itemset Mining Algorithm Using a Novel Three-Dimensional Itemset Matrix and Vectors 5. Collaborative Filtering Algorithm Integrating Penalty Factors and Temporal Weighting 6. Collaborative Filtering Algorithm Based on User Attributes and Item Ratings 7. Prototype ...Full description
1. Introduction 2. Theoretical Foundations of Machine Learning 3. Theoretical Foundations of Personalized Recommendation Algorithms 4. A Frequent Itemset Mining Algorithm Using a Novel Three-Dimensional Itemset Matrix and Vectors 5. Collaborative Filtering Algorithm Integrating Penalty Factors and Temporal Weighting 6. Collaborative Filtering Algorithm Based on User Attributes and Item Ratings 7. Prototype System for Personalized Book Recommendation 8. Conclusions and Future Work