Abstract
This paper put forward the concept of OEM model with weight on its edges, developes a new approach to extracting schema from semistructured data with weight on its edges, and gives two theorems related to computing taget set of label path and suporting degree of label path. Using wideth-first and top-down traversing strategy ,the algorithm computes target set and supporting degree of every label in a label path, and decides whether the label is retained in schema model according to its magnitude of supporting degree and weight of the label .In the last, we test the validity and efficiency of the algorithm. The schema scale of the semistructured data obtained from the same OEM database in this paper is smaller than that in other paper.
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Li, J., Shi, S. (2009). Extracting Schema from Semistructured Data with Weight Tag. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_126
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DOI: https://doi.org/10.1007/978-3-642-01513-7_126
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01512-0
Online ISBN: 978-3-642-01513-7
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