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arXiv Machine Learning By Evgeniia Kositsyna, Jorge Lloret-Gazo

Web Price Extraction: State of the Art and an Adaptive Browserless Implementation

Read the original on arXiv Machine Learning →

The paper presents an adaptive browserless system for extracting prices from e‑commerce websites, improving robustness to structural differences. It combines HTML fragmentation with syntactic, semantic, and frequency rules, then enhances the baseline with a Bayesian weight‑update and a genetic‑algorithm parameter optimizer. The hybrid approach raises precision from 77.2% to 87.3% and cuts per‑page processing time by about 14%, positioning it as a competitive, low‑cost alternative to manual wrappers, browser‑based, or LLM‑driven methods.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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