2009
DOI: 10.1016/j.datak.2009.01.001
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Improving XML schema matching performance using Prüfer sequences

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Cited by 41 publications
(30 citation statements)
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“…Note that the issue of integrating structural and semantic similarity evaluation has also been investigated in the contexts of schema matching/integration [3,4,18], as well as ontology mapping/mediation [46,51,52]. Yet, while comparable to tree-based XML documents, schemas and ontologies often underline more intricate graph structures, and thus require graph-based algorithms and heuristics in evaluating similarity, which are out of the scope of this paper (here, we limit our presentation to XML tree-based approaches).…”
Section: Discussionmentioning
confidence: 99%
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“…Note that the issue of integrating structural and semantic similarity evaluation has also been investigated in the contexts of schema matching/integration [3,4,18], as well as ontology mapping/mediation [46,51,52]. Yet, while comparable to tree-based XML documents, schemas and ontologies often underline more intricate graph structures, and thus require graph-based algorithms and heuristics in evaluating similarity, which are out of the scope of this paper (here, we limit our presentation to XML tree-based approaches).…”
Section: Discussionmentioning
confidence: 99%
“…As for precision, our method tends to yield average levels that are identical to those attained using existing comparison methods, which is underlined in the results corresponding to sets S 2 , S 3 , S 5 , and S 6 . In a few cases, it achieved lower precision, i.e., with sets S 1 and S 4 .…”
Section: Xml Document Clustering Experimentsmentioning
confidence: 99%
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“…The approach consists of two stages: Prüfer Sequence Construction and Similarity computation. 3 . The Pre-processing phase is considered with the representation of each abstract item (subtree) as a sequence representation using the Prüfer encoding method.…”
Section: Abstract Matchingmentioning
confidence: 99%
“…Let n be the average operation size, k be the average operation number, and S be the number of input WSs. Following the same process in [3], it can be proven that the overall worst-case time complexity of the schema matching algorithm between two WSs is O(n 2 k 2 ) .…”
Section: Ssimm[i J] = Combines(child(ni Nj ) Leaf(ni Nj) Ancestomentioning
confidence: 99%