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Development of a Personalized Book Recommendation System for Children Using Machine Learning
  1. case
  2. Development of a Personalized Book Recommendation System for Children Using Machine Learning

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Development of a Personalized Book Recommendation System for Children Using Machine Learning

blink22.com
Education
Consumer products & services

Challenges in Personalized Book Discovery for Children

Digitized books are more engaging for children than traditional books, but finding the right content to maintain their interest is difficult. Existing AI models for personalized recommendations were insufficient, requiring the development of a custom solution to analyze vast datasets and deliver rapid, age-appropriate suggestions.

About the Client

Digital library and book recommendation app leveraging machine learning to provide personalized Arabic-language content for children.

Objectives for AI-Driven Recommendation System

  • Develop a machine learning-powered book recommender system capable of analyzing thousands of data points.
  • Deliver personalized reading recommendations for children based on interests, age, and learning styles.
  • Process terabytes of unstructured data in seconds to ensure real-time responsiveness.
  • Establish a scalable solution adaptable to multiple age ranges and life stages.

Core Functionalities for Book Recommendation Platform

  • User profile creation for tracking child interests and reading history.
  • Machine learning-driven recommendation engine with dynamic updates.
  • Multilingual support (starting with Arabic language content).
  • Real-time data processing for instant recommendation generation.
  • Age-range filtering and learning style adaptation.

Technologies for Data Processing and Machine Learning

BigQuery
TensorFlow
Python ML
Apache Beam

System Integrations

  • Third-party analytics platforms
  • Content delivery networks (CDNs) for media streaming

Non-Functional Requirements

  • Scalability to handle terabytes of unstructured data.
  • High-performance processing for sub-second recommendation delivery.
  • Data security and privacy compliance for child users.
  • Reliability in recommendation accuracy across diverse content types.
  • User-friendly interface for parents and children.

Expected Business and Educational Impact

Transform Noory into a leading educational tool by making reading more engaging for children through hyper-personalized recommendations. Enable parents to effortlessly discover age-appropriate content, driving user retention and positioning Noory as a market leader in Arabic-language children's digital libraries.

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