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Inferring Structure in Semistructured Data

Nestorov, S. and Abiteboul, S. and Motwani, R. (1997) Inferring Structure in Semistructured Data. In: Workshop on Management of Semistructured Data, May 1997, Tucson, Arizona.




When dealing with semistructured data such as that available on the Web, it becomes important to infer the inherent structure, both for the user (e.g., to facilitate querying) and for the system (e.g., to optimize In this paper, we consider the problem of identifying some underlying structure in large collections of semistructured data. Since we expect the data to be fairly irregular, this structure consists of an approximate classication of objects into a hierarchical collection of types. We propose a notion of a type hierarchy for such data, an algorithm for deriving the type hierarchy, and rules for assigning types to data elements.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:semistructured data, classification, type inference
Subjects:Computer Science > Semistructured Data
Related URLs:Project Homepage
ID Code:248
Deposited By:Import Account
Deposited On:25 Feb 2000 16:00
Last Modified:04 Jan 2009 12:01

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