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Description
Important Points to Note
- I agree to adhere to the project's Code of Conduct.
- I have reviewed and understood the project's Contributing Guidelines.
- I have checked the existing issues and can confirm that this is not a duplicate.
- I have reviewed and understood the project's Issue Creation Guidelines.
Category
Feature Addition
Enhancement Description
Introduce an intelligent recommendation system that curates a personalized learning feed for each user. Based on their interaction history, skill level, and preferred domains (e.g., Web Dev, DSA, AI/ML), the system will suggest relevant blogs, projects, and coding challenges—making Code-A2Z feel like a tailored mentor.
🚨 Problem Statement
Currently, all users see the same homepage and content suggestions, regardless of their background or goals. This leads to:
- Content Overload: Beginners may feel overwhelmed by advanced topics.
- Low Engagement: Users skip content that doesn’t match their interests.
- Missed Opportunities: High-value resources go unnoticed by the right audience.
🤖 AI-Driven Solution
Build a recommendation engine that uses user metadata and activity logs to personalize the experience.
🔍 Smart Algorithm - Content-Based Filtering: Match tags, keywords, and categories with user preferences.
- User Clustering: Group users by behavior and recommend what similar users liked.
- Skill-Level Detection: Use quiz scores, completed projects, and time-on-page to infer skill level.
AI Feedback Loop (Planned) - Users can rate recommendations (👍/👎).
- System learns from feedback to refine future suggestions.
- Admin dashboard shows top-performing content per user cluster.
Screenshots or Logs
Screenshots / Logs (To Be Included in Final PR)
- Personalized feed showing recommended blogs/projects.
- Logs of user interaction and recommendation triggers.
- Feedback analytics showing improvement in engagement.
Priority
Up to 2 days
Open Source Program
GSSoC
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Status
backlog