Volume 10, Number 5

Developing Products Update-Alert System for E-Commerce Websites Users
using Html Data and Web Scraping Technique

  Authors

Ikechukwu Onyenwe, Ebele Onyedinma, Chidinma Nwafor and Obinna Agbata, Nnamdi Azikiwe University, Nigeria

  Abstract

Websites are regarded as domains of limitless information which anyone and everyone can access. The new trend of technology has shaped the way we do and manage our businesses. Today, advancements in Internet technology has given rise to the proliferation of e-commerce websites. This, in turn made the activities and lifestyles of marketers/vendors, retailers and consumers (collectively regarded as users in this paper) easier as it provides convenient platforms to sale/order items through the internet. Unfortunately, these desirable benefits are not without drawbacks as these platforms require that the users spend a lot of time and efforts searching for best product deals, products updates and offers on ecommerce websites. Furthermore, they need 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 obtain HTML data for identifying products updates based on the current time. These HTML data are preprocessed to extract details of the products such as name, price, post date and time, etc. to serve as useful information for users.

  Keywords

NATURAL LANGUAGE PREPROCESSING (NLP), E-COMMERCE, E-RETAIL, HTML, DATA, Web, Webscrapping