[Feature]: Project Recommendation Service

[SudiptaPaul-31]

🔍 Problem Statement

Description

Create a backend service that recommends relevant projects to freelancers based on their profile. Recommendations should leverage skills, previous projects, budget preferences, and project categories to improve discovery and matching.

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Considerations

• Skills — match freelancer skill tags with project requirements.
• Previous projects — prioritize projects similar to past successful work.
• Budget — align recommendations with freelancer’s preferred budget range.
• Project category — filter by categories relevant to freelancer expertise.

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Tasks

• Design recommendation algorithm — combine weighted factors (skills, history, budget, category).
• Implement efficient database queries — use indexes and optimized joins for scalability.
• Add pagination support — return results in chunks for large datasets.
• Fallback logic — when insufficient matching data exists, recommend recent or trending projects.
• Expose API endpoint — provide a REST/GraphQL endpoint for fetching recommendations.
• Add caching layer — reduce load for frequently requested recommendations.
• Include logging/metrics — track recommendation quality and query performance.

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Acceptance Criteria

• ✅ Paginated recommendations — API returns results in pages with metadata (totalCount, hasMore).
• ✅ Efficient database queries — recommendations load quickly even under high traffic.
• ✅ Fallback to recent projects when insufficient matching data exists.
• ✅ Consistent results across sessions — same profile yields stable recommendations.
• ✅ Secure access control — only authenticated freelancers can request recommendations.
• ✅ Unit/integration tests included — validate algorithm correctness and performance.

📈 Expected Impact

High — Would significantly improve user experience

[collins-uzu]

@collins-uzu has applied to work on this issue as part of the Stellar Wave Program's 8th wave.

Hello, I have reviewed the issue and understand what needs to be done.

I would appreciate being assigned to it.

ℹ️ Repo Maintainers: To accept this application, review their application or assign @collins-uzu to this issue.