Social Trust Recommendation Algorithm Based on Probability Matrix Factorization

目录

声明

Abstract

Table of contents

Chapter 1 Introduction

1．1 Research Background and Significance

1．2 Research Status

1．3 The Main Contribution and Innovation of thesis

1．4 Structure of the thesis

Chapter 2Recommendation System and Related Theoretical Basis

2．1 Content-based Recommendation Algorithm

2．2 Recommendation Algorithm based on Collaborative fil-tering

2．2．1 Neighborhood-based Recommendation Algorithm

2．2．2 Recommendation Algorithm based on Matrix Factorization

2．3 Hybrid Filtering Recommendation Algorithm

2．4 Common data set

2．5 Summary of this Chapter

Chapter 3Social Trust Recommendation combine with Social Regularization

3．1 Research Motivation

3．2 Social Trust Recommendation Model combine with So-cial Regularization

3．2．1 Probabilistic Matrix Factorization

3．2．2 Social Network Matrix Factorization

3．2．3 Social Regularization

3．2．4 Finel Combined Model

3．3 Experiment and Results Analysis

3．3．1 Experimental Environment

3．3．2 Data Sets

3．3．3 Comparative Experiment

3．3．4 Setting the Value of the Parameter λC

3．3．5 Setting the Value of the Parameter β

3．4 Summary of this Chapter

Chapter 4Social Recommendation based on Dynamic Difference Trust

4．1 Research Motivation

4．2．1 Probability Matrix Factorization Model Based on Trust Relation-ship

4．2．2 Social Trust Based on User Difference Trust

4．2．3 Final Combined Model

4．3 Experiment and Analysis

4．3．1 Experimental Environment and Data Set

4．3．2 Comparative Experiment

4．3．3 Influence of Social Regularization Parameter β

4．4 Recommended System

4．4．1 Demand Analysis

4．4．2 Functional Design

4．4．3 System Implementation

4．5 Summary of this Chapter

Chapter 5Summary And Outlook

5．1 Summary of the Methods in this thesis

5．2 Work Prospects

References

Acknowledgements

Appendix A