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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM68478

SMART SCHEME & SCHOLARSHIP RECOMMENDATION PORTAL

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM68478

Volume:

10 |

10 |

Oct 2026

Pages:

1-17

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM68478

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

B Sanjay Krishna

B Sanjay Krishna

Department of Computer Science and Engineering

SRI SHAKTHI INSTITUTE OF ENGINEERING AND TECHNOLOGY

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MANISH BHARATHI G

MANISH BHARATHI G

Department of Computer Science and Engineering

SRI SHAKTHI INSTITUTE OF ENGINEERING AND TECHNOLOGY

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NAVIN R

NAVIN R

Department of Computer Science and Engineering

SRI SHAKTHI INSTITUTE OF ENGINEERING AND TECHNOLOGY

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MAVYASHRI M

MAVYASHRI M

Department of Computer Science and Engineering

SRI SHAKTHI INSTITUTE OF ENGINEERING AND TECHNOLOGY

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MOHAMED FAIZAL S

MOHAMED FAIZAL S

Department of Computer Science and Engineering

SRI SHAKTHI INSTITUTE OF ENGINEERING AND TECHNOLOGY

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Abstract

The Smart Scheme & Scholarship Recommendation Portal is a decision-support web platform that helps students and citizens discover government schemes, scholarships, welfare programmes, subsidies and educational benefits for which they may qualify. Information about such benefits is spread across many ministries, departments and portals, and eligibility conditions are often written in dense administrative language. As a result, eligible people frequently do not apply. The portal addresses this by combining a verified scheme catalogue, a structured citizen profile and a deterministic eligibility engine that explains every outcome in plain language. The eligibility engine evaluates each scheme’s rules against normalised citizen facts using three-valued (Kleene) logic, so that missing information produces an explicit “unknown” instead of a silent pass or fail. Every scheme is classified as Eligible, Likely Eligible, Needs Verification or Not Eligible, with matched, failed and unknown conditions listed. A document vault supports secure upload, signature-checked storage, field extraction and consent-based confirmation of extracted values. A notification module issues deadline, opening and document-expiry alerts. A grounded AI assistant explains results and guides applications, but it is never allowed to decide eligibility. An analytics and audit module gives administrators platform insight and an append-only security trail. The system is a modular monolith built with React 18, TypeScript, Vite and Tailwind CSS on the frontend, and Node.js, Express, Prisma and PostgreSQL on the backend. It uses short-lived JSON Web Tokens with rotating refresh tokens, bcrypt password hashing, role-based access control, Helmet, strict CORS, rate limiting, structured logging and Docker-based deployment. The repository records 146 backend and 64 frontend automated tests, a seed catalogue of 162 schemes across 14 categories, and ten completed modules. These results describe software behaviour; they are not an independent measurement of recommendation accuracy, and the portal gives indicative guidance only. Final approval always rests with the responsible department or institution.

KEYWORDS

scheme recommendation scholarship discovery rule-based eligibility three-valued logic explainable decision support grounded AI assistant document vault role-based access control e-governance.

Cite This Article

B Sanjay Krishna, MANISH BHARATHI G, NAVIN R, MAVYASHRI M, MOHAMED FAIZAL S, "SMART SCHEME & SCHOLARSHIP RECOMMENDATION PORTAL," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 10, pp. 1-17, Oct 2026. https://doi.org/10.55041/IJSREM68478

Full Article/Conclusion

The Smart Scheme & Scholarship Recommendation Portal shows one workable way to help citizens find and prepare for government benefits while remaining trustworthy. Its core is a deterministic, explainable eligibility engine that uses three-valued logic, so that a missing fact becomes an explicit request for information instead of a misleading verdict. Around this core, the system provides a verified, versioned scheme catalogue, a structured and consent-based citizen profile, a secure document vault with a mandatory confirmation step, scheduled deadline and expiry notifications, a grounded AI assistant that may explain but never decide, and administrative analytics with an append-only audit trail. The architecture is a modular monolith in React, TypeScript, Express, Prisma and PostgreSQL, organised into ten modules with a deliberate separation between ground truth and assistance. This separation allows assistive components such as the AI provider or OCR engine to fail without affecting discovery or eligibility. Security and operational concerns are treated as design requirements, with short-lived and rotating tokens, role-based access, validated input, hardened headers, rate limiting, redacted logging, containerised deployment, backups and a documented recovery plan. The repository records 210 automated tests and a zero-warning lint policy. The work also has clear boundaries. The document extraction provider is currently a heuristic stand-in, rules have not been validated by awarding authorities, and no user study, load test or penetration test has been performed. The portal’s guidance is indicative, and final decisions remain with the responsible departments and institutions. Within these limits, the project shows that explainable rule evaluation, careful handling of missing information and restricted use of AI can be combined into a platform that is both useful and honest about what it does not know

References

[1] S. C. Kleene. Introduction to Metamathematics. North-Holland, Amsterdam, 1952. [2] F. Ricci, L. Rokach and B. Shapira (eds.). Recommender Systems Handbook, 2nd ed. Springer, 2015. [3] P. Lewis et al. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. Advances in Neural Information Processing Systems, 33, 2020, pp. 9459-9474. https://arxiv.org/abs/2005.11401 [4] Tesseract OCR contributors. Tesseract User Manual. Official documentation. https://tesseract-ocr.github.io/tessdoc/ [5] OWASP Foundation. OWASP Top 10 Web Application Security Risks. https://owasp.org/www-project-top-ten/ [6] M. Jones, J. Bradley and N. Sakimura. JSON Web Token (JWT). RFC 7519, IETF, 2015. https://www.rfc-editor.org/rfc/rfc7519 [7] N. Provos and D. Mazieres. A Future-Adaptable Password Scheme. Proceedings of the USENIX Annual Technical Conference, 1999. [8] Government of India. The Digital Personal Data Protection Act, 2023. Ministry of Electronics and Information Technology. [9] Meta Open Source. React Documentation. https://react.dev [10] Government of India. National Scholarship Portal. https://scholarships.gov.in

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Publication Date

10/29/2026

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Double-Blind Peer Review

Review Rounds: 2

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