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Measuring the Structural Similarity of Semistructured Documents Using Entropy

Summary: Entropy-based measure of structural similarity for semistructured documents using extracted structure and Ziv-Lempel or Ziv-Merhav crossparsing to compute entropy. Claims the first linear-time approach for this problem, with clustering results rivaling existing methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9703
Venue
VLDB
Year
2007
Pagerank
5.3516704e-05
Overall Rank
8,882 | 39.07%
DOI
10.14778/1325851.1325967

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{helmer_vldb07,
        title = {{Measuring the Structural Similarity of Semistructured Documents Using Entropy}},
        author = {Helmer, Sven},
        journal = {PVLDB},
        series = {{VLDB} '07},
        pages = {1022--1033},
        doi = {10.14778/1325851.1325967},
        url = {https://doi.org/10.14778/1325851.1325967},
        year = {2007}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
3,651 Keyword Search over Relational Databases: A Metadata Approach 2011 SIGMOD 7.2249652e-05
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Outgoing Citations (Sorted by Pagerank)

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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