Contents
- Introduction 2
- Related work 2
- Phases of recommendation process 2
3.1. Information collection phase 2
3.1.1. Explicit feedback 2
3.1.2. Implicit feedback 2
3.1.3. Hybrid feedback 2
3.2. Learning phase 2
3.3. Prediction/recommendation phase 2
- Recommendation filtering techniques 2
4.1. Content-based filtering 2
4.1.1. Pros and Cons of content-based filtering techniques 2
4.1.2. Examples of content-based filtering systems 2
4.2. Collaborative filtering 2
4.2.1. Memory based techniques 2
4.2.2. Model-based techniques 2
4.2.3. Pros and Cons of collaborative filtering techniques 2
4.2.4. Examples of collaborative systems 2
4.2.5. Trust in collaborative filtering recommendation systems 2
4.3. Hybrid filtering 2
4.3.1. Weighted hybridization 2
4.3.2. Switching hybridization 2
4.3.3. Cascade hybridization 2
4.3.4. Mixed hybridization 2
4.3.5. Feature-combination 2
4.3.6. Feature-augmentation 2
4.3.7. Meta-level 2
- Evaluation metrics for recommendation algorithms 2
- Conclusion 2
References 2
- Introduction
- Related work
- Phases of recommendation process
3.1. Information collection phase
3.1.1. Explicit feedback
3.1.2. Implicit feedback
3.1.3. Hybrid feedback
3.2. Learning phase
3.3. Prediction/recommendation phase
- Recommendation filtering techniques
4.1. Content-based filtering
4.1.1. Pros and Cons of content-based filtering techniques
4.1.2. Examples of content-based filtering systems
4.2. Collaborative filtering
4.2.1. Memory-based techniques
4.2.2. Model-based techniques
4.2.3. Pros and Cons of collaborative filtering techniques
4.2.4. Examples of collaborative systems
4.2.5. Trust in collaborative filtering recommendation systems
4.3. Hybrid filtering
4.3.1. Weighted hybridization
4.3.2. Switching hybridization
4.3.3. Cascade hybridization
4.3.4. Mixed hybridization
4.3.5. Feature-combination
4.3.6. Feature-augmentation
4.3.7. Meta-level
- Evaluation metrics for recommendation algorithms
- Conclusion
References
