Developing Products Update-Alert System for e-Commerce Websites Users Using HTML Data and Web Scraping Technique

TL;DR

This paper presents a system that uses web scraping and HTML data analysis to provide real-time product update alerts for e-commerce website users, helping them save time and find deals more efficiently.

Contribution

It introduces a novel approach combining web scraping and HTML data processing to detect product updates on e-commerce sites for user alerts.

Findings

Successfully extracted product details like name, price, and post date from HTML data.

Enabled real-time detection of product updates on e-commerce websites.

Improved user experience by reducing search time for product deals.

Abstract

Websites are regarded as domains of limitless information which anyone and everyone can access. The new trend of technology put us to change the way we are doing our business. The Internet now is fastly becoming a new place for business and the advancement in this technology gave rise to the number of e-commerce websites. This made the lifestyle of marketers/vendors, retailers and consumers (collectively regarded as users in this paper) easy, because it provides easy platforms to sale/order items through the internet. This also requires that the users will have to spend a lot of time and effort to search for the best product deals, products updates and offers on e-commerce websites. They have to filter and compare search results by themselves which takes a lot of time and there are chances of ambiguous results. In this paper, we applied web crawling and scraping methods on an e-commerce website to get HTML data for identifying products updates based on the current time. The HTML data is preprocessed to extract details of the products such as name, price, post date and time, etc. to serve as useful information for users.