Year: 2025
Type: conference-paper
Abstract: Tools designed to extract main content from web pages require thorough evaluation, yet existing benchmarks disproportionately focus on English-language datasets. Consequently, previous studies have shown that while these extractors are well-optimized for English, their effectiveness partially or entirely diminishes in other languages. This study reproduces and extends recent benchmarks by incorporating multilingual datasets as a key factor. We analyze extractor performance across five languages-Greek, English, Polish, Russian, and Chinese-highlighting the need to adapt extraction models to linguistic variations. Our results show that while some extractors maintain stable performance, others suffer significant drops in precision and recall on non-English or structurally irregular pages.
Institution: Université de Caen Normandie
Language: English
Topic: Web Data Mining and Analysis
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Funder: Universitas Brawijaya
OpenAlex ID: W4412377994