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Introduction:

Online dating has become a popular way for individuals to meet potential partners due to the convenience and accessibility of dating platforms. With the vast number of users on these platforms, it can be overwhelming for individuals to find compatible matches. Recommender systems are increasingly being used in online dating platforms to help users find potential matches based on their preferences and interactions with the system.

Background of study:

The use of recommender systems in online dating platforms has gained traction in recent years due to advancements in technology and the increasing demand for personalized recommendations. These systems analyze user preferences and interaction data to suggest potential matches, increasing the likelihood of successful connections.

Problem Statement:

Despite the popularity of online dating platforms, users often struggle to find compatible matches due to the overwhelming number of options available. Recommender systems can help alleviate this issue by providing personalized recommendations based on user preferences and interaction data.

Objective of study:

The objective of this study is to explore the effectiveness of recommender systems in online dating platforms in facilitating successful matches based on user preferences and interaction data.

Limitation of study:

One limitation of this study is the reliance on self-reported user preferences, which may not always accurately reflect individual preferences. Additionally, external factors such as cultural norms and societal expectations may impact the effectiveness of recommender systems in online dating.

Scope of study:

This study will focus on the use of recommender systems in online dating platforms and their impact on facilitating successful matches based on user preferences and interaction data. The study will not delve into the ethical implications of using recommender systems in online dating.

Significance of study:

This study is significant as it adds to the existing literature on recommender systems in online dating platforms and provides insights into how these systems can be effectively used to facilitate successful matches based on user preferences and interaction data.

Structure of the Thesis:

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 in online dating
2.2 User preferences in online dating
2.3 Interaction data in online dating
2.4 Effectiveness of recommender systems in online dating
2.5 Challenges in using recommender systems in online dating

Chapter 3: Research Methodology
3.1 Research design
3.2 Data collection methods
3.3 Data analysis
3.4 Sampling techniques
3.5 Research ethics
3.6 Study limitations
3.7 Research validity
3.8 Research reliability

Chapter 4: Discussion of Findings
4.1 Analysis of user preferences in online dating
4.2 Evaluation of interaction data in online dating
4.3 Effectiveness of recommender systems in online dating
4.4 Comparison of different recommender systems
4.5 Implications for online dating platforms

Chapter 5: Conclusion and Summary
5.1 Summary of findings
5.2 Conclusion
5.3 Recommendations for future research

Thesis Overview:

Recommender systems have revolutionized the way individuals find potential matches on online dating platforms. By analyzing user preferences and interaction data, these systems provide personalized recommendations that increase the likelihood of successful connections. This thesis aims to explore the effectiveness of recommender systems in online dating platforms in facilitating successful matches based on user preferences and interaction data. The study will contribute to the existing literature on recommender systems in online dating and provide insights into how these systems can be leveraged to enhance the user experience and improve match quality. Through a comprehensive review of the literature, research methodology, discussion of findings, and conclusion, this thesis will provide a comprehensive analysis of the role of recommender systems in online dating using user preferences and interaction data.

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