2009 ExtractingOutputMetadataFr

• (Wang & Agrawal, 2009) ⇒ Fan Wang, Gagan Agrawal. (2009). “Extracting Output Metadata from Scientific Deep Web Data Sources.” In: Proceedings of the Ninth IEEE International Conference on Data Mining (ICDM 2009). doi:10.1109/ICDM.2009.41

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Abstract

• Increasingly, many data sources appear as online databases, hidden behind query forms, thus forming the deep Web. The popularity of this new medium for data dissemination is leading to new problems in data integration. Particularly, to enable data integration from multiple deep Web data sources, one needs to obtain the metadata for each of the data sources. Obtaining the metadata, particularly, the output schema, can be very challenging. This is because, given an input query, many deep web data sources only return a subset of the output schema attributes, i.e, the ones that have a non-NULL value for the corresponding input. In this paper, we propose two approaches, which are the sampling model approach and the mixture model approach, respectively, to efficiently obtain an approximately complete set of output schema attributes from a deep Web data source. Our experiments show while each of the above two approaches has limitations, a hybrid strategy, where we combine the two approaches, achieves high recall with good precision for most data sources.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2009 ExtractingOutputMetadataFr	Fan Wang Gagan Agrawal			Extracting Output Metadata from Scientific Deep Web Data Sources		ICDM 2009 Proceedings		10.1109/ICDM.2009.41		2009