Abstract
A main challenge in wrapping web data is to make wrappers robust w.r.t. variations in HTML sources, reducing human effort as much as possible. In this paper we develop a new approach to speed up the specification of robust wrappers, allowing the wrapper designer to not care about detailed definition of extraction rules. The key-idea is to enable a schema-based wrapping system to automatically generalize an original wrapper w.r.t. a set of example HTML documents. To accomplish this objective, we propose to exploit the notions of extraction rule and wrapper subsumption for computing a most general wrapper which still shares the extraction schema with the original wrapper, while maximizes the generalization of extraction rules w.r.t. the set of example documents.
Work supported by a MIUR grant under the project “GeoPKDD – Geographic Privacy-aware Knowledge Discovery and Delivery”, 2004.
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Fazzinga, B., Flesca, S., Tagarelli, A. (2005). Learning Robust Web Wrappers. In: Andersen, K.V., Debenham, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2005. Lecture Notes in Computer Science, vol 3588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546924_72
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DOI: https://doi.org/10.1007/11546924_72
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