Real-Time Laptop Price Prediction through Web Data Analysis

DOI

10.2991/978-94-6463-858-5_115How to use a DOI?

Keywords

Laptop Price Prediction; Machine Learning; Web Scraping; Regression Models; Real-Time Price Tracking; E-Commerce Analytics

Abstract

The rapid rise of e-commerce is making price fluctuations a major challenge to consumers seeking to make informed purchasing decisions. In this study, we propose a machine learning-based laptop price prediction model, in conjunction with web scraping, that collects real-time price data from multiple e-commerce platforms. Based on key specifications such as processor, RAM, storage, GPU, and brand, regression models such as Linear Regression, Random Forest, and XGBoost Incorporated predict laptop prices. In previous studies, machine learning has been shown to be effective in price estimation, and web scraping has proven useful for real-time data collection. However, existing solutions often rely upon static datasets, inhibiting their ability to reflect market trends dynamically. The proposed system continuously updates its predictions through real-time price tracking with historical trend analysis, thus providing users with personalized price estimations and purchasing recommendations. The experimental results show that Random Forest outperforms traditional regression models and provides higher prediction accuracy. Being scalable, the system will be readily extended to other electronic products in the future. This research contributes to the field of e-commerce analytics through the presentation of a dynamic, data-driven approach to predicting laptop prices while increasing transparency and helping consumerism make cost-effective decisions.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - G. Anudeep Goud
AU  - B. Tanishqi
AU  - B. Hemanth Reddy
AU  - G. Tanish Bhargav
PY  - 2025
DA  - 2025/11/04
TI  - Real-Time Laptop Price Prediction through Web Data Analysis
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 1383
EP  - 1392
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_115
DO  - 10.2991/978-94-6463-858-5_115
ID  - Goud2025
ER  -