Book Recommendation Integrating Book Category Features and User Attribute Information

Project Code :TCMAFS1345

Objective

The objective of this project is to build a smart online book recommendation app that gives every reader perfect book suggestions even when very few people have rated anything. The app cleverly mixes who the reader is (their age, gender and job) with what each book is about (its four clear categories such as History, Romance, Science or Mystery), sends both details to Google Gemini AI, which instantly turns them into hidden numbers, measures how close the reader is to every book, and returns the best matches along with one short reason like “Sapiens–because you love History & Science” or “1984 – perfect for your interest in Politics & Dystopia”, so every click delivers spot-on tips that feel personal and exciting.

Abstract

This project presents a smart, AI-powered online book recommendation middleware platform that delivers highly personalized book suggestions by intelligently combining user demographic attributes (age, gender, occupation) with rich book category features (four distinct categories per book). The system allows administrators to securely manage the entire book catalog while registered users receive instant, top-10 tailored book recommendations generated by Google Gemini AI — even in cold-start scenarios with minimal or zero rating history. Each recommendation is accompanied by a clear, human-readable one-line reason (e.g., “Sapiens – because you love History & Science”). Users can explore, search, rate books, and instantly improve future recommendations through their ratings. Built as a scalable, secure, and JSON-safe middleware with RESTful APIs, the platform can be seamlessly integrated into any web, mobile, or third-party application requiring intelligent book discovery, making personalized reading feel exciting, relevant, and effortless.

Keywords: Book Recommendation System, Content-Based Filtering, User Attribute Profiling, Multi-Category Tagging, Cold-Start Recommendation, Google Gemini AI Integration, Personalized Reasoning, Middleware Platform, Collaborative-Content Hybrid (Future-Ready)

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.