Online Shopping Item Cost Analysis through Web Scraping and Nodejs


Authors : Dr.K V Nagendra; Dr.M.Ussenaiah

Volume/Issue : Volume 9 - 2024, Issue 6 - June

Google Scholar : https://tinyurl.com/3bsjbykz

Scribd : https://tinyurl.com/438djm9a

DOI : https://doi.org/10.38124/ijisrt/IJISRT24JUN1016

Abstract : The swift expansion of online shopping platforms has resulted in a wide variety of products being available for purchase online, necessitating the development of effective tools for comparing prices. This initiative suggests a solution that makes use of web scraping methods and the Node.js framework to gather and examine the prices of products from various online stores. The system will make use of web scraping tools to pull out important pricing data from selected websites, and Node.js will be used for the processing and comparison of this data. The goal of this project is to create an easy-to-use interface that allows customers to input details about a product and get detailed price comparisons from various online sellers. Through this project, we aim to equip consumers with useful information to make well-informed buying choices in the competitive online shopping market.

Keywords : E-Commerce, Web Scraping, Node.js, Data Processing, Consumers.

References :

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  2. Cantelon, G., Harter, M., & Rajlich, M. (2017). "Node.js in Action." Manning Publications.
  3. Nock, R. (2018). "Web Scraping with Python: A Guide to Data Mining the Modern Web." O'Reilly Media.
  4. Mehta, A. (2019). "Mastering Node.js: Build robust and scalable real-time server-side web applications." Packt Publishing.
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  8. Lawson, R. (2018). "Web Scraping with Python and BeautifulSoup." Apress.
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  10. Data Protection Authority. (2022). "Guidelines on Web Scraping and Privacy." [Online] Available at: https://www.dataprotectionauthority.com/guidelines/web- scraping-privacy/
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  12. Jiahao Wu, “Web Scraping using Python: Step by step guide” ResearchGate publications (2019).
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The swift expansion of online shopping platforms has resulted in a wide variety of products being available for purchase online, necessitating the development of effective tools for comparing prices. This initiative suggests a solution that makes use of web scraping methods and the Node.js framework to gather and examine the prices of products from various online stores. The system will make use of web scraping tools to pull out important pricing data from selected websites, and Node.js will be used for the processing and comparison of this data. The goal of this project is to create an easy-to-use interface that allows customers to input details about a product and get detailed price comparisons from various online sellers. Through this project, we aim to equip consumers with useful information to make well-informed buying choices in the competitive online shopping market.

Keywords : E-Commerce, Web Scraping, Node.js, Data Processing, Consumers.

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