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Development of a recommendation system for personalized book recommendations

 

Table Of Contents


1. Introduction
  1.1 Background
  1.2 Motivation
  1.3 Objectives
2. Literature Review
  2.1 Recommendation Systems
  2.2 Content-Based Filtering
  2.3 Collaborative Filtering
  2.4 Related Work
3. Data Collection and Preprocessing
  3.1 User Preferences
  3.2 Book Metadata
  3.3 Data Cleaning and Transformation
4. Recommendation Algorithm
  4.1 Content-Based Filtering
  4.2 Collaborative Filtering
  4.3 Hybrid Approaches
5. System Implementation
  5.1 User Interface Design
  5.2 Backend Architecture
  5.3 Integration with Book Databases

Thesis Abstract

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.

Thesis Overview

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