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Bibliografiske detaljer
Main Authors: Kalva, Ajay Kumar, Namburu, Yogi Venkata Satyanarayana, Karri, Jeevan Kumar, Pentyala, Navyanth
Format: Recurso digital
Sprog:engelsk
Udgivet: Zenodo 2025
Fag:
Online adgang:https://doi.org/10.5281/zenodo.17618682
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author Kalva, Ajay Kumar
Namburu, Yogi Venkata Satyanarayana
Karri, Jeevan Kumar
Pentyala, Navyanth
author_facet Kalva, Ajay Kumar
Namburu, Yogi Venkata Satyanarayana
Karri, Jeevan Kumar
Pentyala, Navyanth
contents <p>This research paper presents the design and implementation of a Personal Portfolio Builder developed using the MERN stack (MongoDB, Express.js, React, and Node.js) with AI integration. The system enables users—especially students, professionals, and freelancers—to create dynamic, customizable portfolio websites without requiring technical expertise. The AI module enhances the process by providing intelligent content recommendations, optimized layouts, skill prioritization, and automated formatting based on best design practices.</p> <p>The paper outlines the system architecture, functional and non-functional requirements, workflow equations, and module-wise design. UML diagrams and flowcharts demonstrate the interaction between the frontend, backend, database, and AI components. The results show that the platform significantly reduces portfolio creation time while improving overall quality and personalization. Future enhancements include NLP-based resume parsing, analytics, expanded templates, and AI chatbot support.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17618682
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle "Personal Portfolio Builder Using MERN Stack With AI Integration"
Kalva, Ajay Kumar
Namburu, Yogi Venkata Satyanarayana
Karri, Jeevan Kumar
Pentyala, Navyanth
MERN Stack
Portfolio Builder
Artificial Intelligence
Web Application
Automation
MongoDB
APIs
ML
DB
<p>This research paper presents the design and implementation of a Personal Portfolio Builder developed using the MERN stack (MongoDB, Express.js, React, and Node.js) with AI integration. The system enables users—especially students, professionals, and freelancers—to create dynamic, customizable portfolio websites without requiring technical expertise. The AI module enhances the process by providing intelligent content recommendations, optimized layouts, skill prioritization, and automated formatting based on best design practices.</p> <p>The paper outlines the system architecture, functional and non-functional requirements, workflow equations, and module-wise design. UML diagrams and flowcharts demonstrate the interaction between the frontend, backend, database, and AI components. The results show that the platform significantly reduces portfolio creation time while improving overall quality and personalization. Future enhancements include NLP-based resume parsing, analytics, expanded templates, and AI chatbot support.</p>
title "Personal Portfolio Builder Using MERN Stack With AI Integration"
topic MERN Stack
Portfolio Builder
Artificial Intelligence
Web Application
Automation
MongoDB
APIs
ML
DB
url https://doi.org/10.5281/zenodo.17618682