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Tree matching techniques have been investigated in many fields, including webdata mining and extraction, as a key component to analyze the content of webdocuments, existing tree matching approaches, like Tree-Edit Distance (TED) orFlexible Tree Matching (FTM), fail to scale beyond a few hundreds of nodes,which is far below the average complexity of existing web online documents andapplications. In this paper, we therefore propose a novel Similarity-basedFlexible Tree Matching algorithm (SFTM), which is the first algorithm to enabletree matching on real-life web documents with practical computation times. Inparticular, we approach tree matching as an optimisation problem and weleverage node labels and local topology similarity in order to avoid anycombinatorial explosion. Our practical evaluation demonstrates that ourapproach compares to the reference implementation of TED qualitatively, whileimproving the computation times by two orders of magnitude.

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