Publication: Measuring structural similarity of semistructured data based on information-theoretic approaches
Measuring structural similarity of semistructured data based on information-theoretic approaches
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Helmer, S., Augsten, N., & Böhlen, M. (2012). Measuring structural similarity of semistructured data based on information-theoretic approaches. The VLDB Journal, 21(5), 677–702. https://doi.org/10.1007/s00778-012-0263-0
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We propose and experimentally evaluate different approaches for measuring the structural similarity of semistructured documents based on information-theoretic concepts. Common to all approaches is a two-step procedure: first, we extract and linearize the structural information from documents, and then, we use similarity measures that are based on, respectively, Kolmogorov complexity and Shannon entropy to determine the distance between the documents. Compared to other approaches, we are able to achieve a linear run-time complexity and
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- Helmer, Sven
- Augsten, Nikolaus
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Helmer, S., Augsten, N., & Böhlen, M. (2012). Measuring structural similarity of semistructured data based on information-theoretic approaches. The VLDB Journal, 21(5), 677–702. https://doi.org/10.1007/s00778-012-0263-0
