Year: 2025
Type: article
Abstract: Web scraping and machine learning (ML) havebroadened price analysis and forecasting by enablingautomated data collection and trend detection. Web scrapingcollects real-time information from online shopping sites toexpose competitive prices and purchasing behaviour. MLalgorithms analyze such information for precise priceforecasting, enabling companies to optimize pricing strategiesand assist customers in making informed purchases. Thisresearch proposes a pricing platform that employs webscraping in online shopping to broaden data collection andanalysis for the assessment of product prices online. Throughpattern and trend detection, the platform enhances marketvisibility, enabling users to monitor price trends and receivethe best prices through an interactive analytics interface. Theresearch proposes a data collection, preprocessing, andanalysis mechanism that enhances the price comparisonplatform. It highlights the benefits of web scraping and ML inenhancing data-driven decision-making and optimizing theonline buying experience.
Authors: Anshika Goel, Ananya Goel, Navjot Kumari, Garima Thakur, Nitu Sangwan, Nidhi Kushwaha
Institution: Chandigarh University
Language: English
Topic: Web Data Mining and Analysis
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409194573