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

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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.

fields

cs.IR 1

years

2024 1

verdicts

REJECT 1

representative citing papers

Movie Recommendation using Web Crawling

cs.IR · 2024-12-14 · reject · novelty 2.0

The paper outlines a hybrid movie recommender that merges static Kaggle data with scraped real-time data, but it provides no evaluation to justify its claim of improved recommendations.

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  • Movie Recommendation using Web Crawling cs.IR · 2024-12-14 · reject · none · ref 13 · internal anchor

    The paper outlines a hybrid movie recommender that merges static Kaggle data with scraped real-time data, but it provides no evaluation to justify its claim of improved recommendations.