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Introduction

Recommender systems have become an essential tool for online retailers to enhance the shopping experience of customers by providing personalized product recommendations based on their browsing and purchase history. These systems utilize customer data to predict their preferences and suggest relevant items, ultimately increasing sales and customer satisfaction. This thesis aims to explore the effectiveness of recommender systems for online shopping using customer browsing and purchase history.

Chapter 1: Introduction

1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review

2.1 Overview of recommender systems
2.2 Types of recommender systems
2.3 Personalization techniques
2.4 Customer browsing behavior
2.5 Customer purchase history
2.6 Impact of recommender systems on online shopping
2.7 Challenges in implementing recommender systems
2.8 Success stories of recommender systems
2.9 Current trends in recommender systems
2.10 Gaps in the existing literature

Chapter 3: Research Methodology

3.1 Research design
3.2 Data collection methods
3.3 Data analysis techniques
3.4 Sampling techniques
3.5 Research variables
3.6 Instrumentation
3.7 Ethical considerations
3.8 Limitations of the research methodology

Chapter 4: Discussion of Findings

4.1 Analysis of customer browsing behavior
4.2 Evaluation of recommender systems
4.3 Comparison of different personalization techniques
4.4 Impact of purchase history on recommendations
4.5 Customer feedback on recommender systems
4.6 Recommendations for improving recommender systems
4.7 Future research directions
4.8 Implications for online retailers

Chapter 5: Conclusion and Summary

In conclusion, this thesis aims to provide valuable insights into the effectiveness of recommender systems for online shopping using customer browsing and purchase history. By examining the impact of these systems on customer satisfaction and sales, retailers can enhance their online shopping experience and drive business growth. The findings of this research will contribute to the existing literature on recommender systems and provide recommendations for future research in this field.

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