Research Paper Collection System Using Web Scrapping

  • Unique Paper ID: 180490
  • PageNo: 1654-1658
  • Abstract:
  • This paper introduces an automated Research Paper Collection System that leverages web scraping techniques to gather and display academic research papers efficiently. Traditional methods of searching for research papers can be time-consuming and inefficient. This system automates the process by extracting relevant metadata, such as titles, authors, publication dates, and abstracts, from academic sources and presenting them on a user-friendly web interface with direct links to the original sources. The system is implemented using BeautifulSoup, which enables dynamic extraction of research paper details from academic websites. The scraped data is structured and displayed on a web-based platform, allowing users to search and filter relevant papers based on keywords. The automated system significantly reduces the time and effort required to locate relevant research papers compared to manual searching. The web interface enhances accessibility by providing direct links, allowing researchers to quickly access full papers from multiple sources. Challenges such as handling dynamic web content and anti-scraping mechanisms were addressed using browser automation techniques. By automating research paper retrieval, this system improves research efficiency and accessibility. Future enhancements may include integrating AI-based filtering, expanding data sources, and optimizing performance for larger datasets.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{180490,
        author = {Prof. Shah Saloni Niranjan and Prof.Nazirkar S.B. and Kakade Shivanjali and Raskar Manjusha and Bhandlakar Pooja},
        title = {Research Paper Collection System Using Web Scrapping},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {1654-1658},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180490},
        abstract = {This paper introduces an automated Research Paper Collection System that leverages web scraping techniques to gather and display academic research papers efficiently. Traditional methods of searching for research papers can be time-consuming and inefficient. This system automates the process by extracting relevant metadata, such as titles, authors, publication dates, and abstracts, from academic sources and presenting them on a user-friendly web interface with direct links to the original sources. The system is implemented using BeautifulSoup, which enables dynamic extraction of research paper details from academic websites. The scraped data is structured and displayed on a web-based platform, allowing users to search and filter relevant papers based on keywords. The automated system significantly reduces the time and effort required to locate relevant research papers compared to manual searching. The web interface enhances accessibility by providing direct links, allowing researchers to quickly access full papers from multiple sources. Challenges such as handling dynamic web content and anti-scraping mechanisms were addressed using browser automation techniques. By automating research paper retrieval, this system improves research efficiency and accessibility. Future enhancements may include integrating AI-based filtering, expanding data sources, and optimizing performance for larger datasets.},
        keywords = {Web scraping, BeautifulSoup, Natural Language Processing, A research automation},
        month = {June},
        }

Cite This Article

Niranjan, P. S. S., & S.B., P., & Shivanjali, K., & Manjusha, R., & Pooja, B. (2025). Research Paper Collection System Using Web Scrapping. International Journal of Innovative Research in Technology (IJIRT), 12(1), 1654–1658.

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