SFTM: Fast Matching of Web Pages using Similarity-based Flexible Tree Matching

Autor: Sacha Brisset, Romain Rouvoy, Lionel Seinturier, Renaud Pawlak
Přispěvatelé: Self-adaptation for distributed services and large software systems (SPIRALS), Inria Lille - Nord Europe, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Cinchéo
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Information Systems
Information Systems, 2023, ⟨10.1016/j.is.2022.102126⟩
ISSN: 0306-4379
DOI: 10.1016/j.is.2022.102126⟩
Popis: International audience; Tree matching techniques have been investigated in many fields, including web data mining and extraction, as a key component to analyze the content of web pages. However, when applied to existing web pages, traditional tree matching approaches, covered by algorithms like Tree-Edit Distance (TED) or XyDiff, either fail to scale beyond a few hundred nodes or exhibit a relatively low accuracy. In this article, we therefore propose a novel algorithm, named Similaritybased Flexible Tree Matching (SFTM), which enables high accuracy tree matching on real-life web pages, with practical computation times. We approach tree matching as an optimisation problem and leverage node labels and local topology similarity in order to avoid any combinatorial explosion. Our practical evaluation demonstrates that SFTM significantly improves the state of the art in terms of accuracy, while allowing computation times significantly lower than the most accurate solutions. By gaining on these two dimensions, SFTM therefore offers an affordable solution to match complex trees in practice.
Databáze: OpenAIRE
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