Development of a recommendation system for personalized book recommendations
Table Of Contents
<p>1. Introduction<br> 1.1 Background<br> 1.2 Motivation<br> 1.3 Objectives<br>2. Literature Review<br> 2.1 Recommendation Systems<br> 2.2 Content-Based Filtering<br> 2.3 Collaborative Filtering<br> 2.4 Related Work<br>3. Data Collection and Preprocessing<br> 3.1 User Preferences<br> 3.2 Book Metadata<br> 3.3 Data Cleaning and Transformation<br>4. Recommendation Algorithm<br> 4.1 Content-Based Filtering<br> 4.2 Collaborative Filtering<br> 4.3 Hybrid Approaches<br>5. System Implementation<br> 5.1 User Interface Design<br> 5.2 Backend Architecture<br> 5.3 Integration with Book Databases<br></p>
Thesis Abstract
<p> Personalized recommendation systems play a vital role in enhancing user experience and engagement in various domains. This project aims to develop a recommendation system specifically tailored for personalized book recommendations. The system will leverage user preferences, reading history, and content analysis to provide accurate and relevant book recommendations to individual users. <br></p>Thesis Overview
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