Nestorov, S. and Abiteboul, S. and Motwani, R. (1997) Inferring Structure in Semistructured Data. SIGMOD Record, 26 (4). pp. 39-43.
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, and outline a method for deriving the type hierarchy, and rules for assigning types to data elements.
|Uncontrolled Keywords:||semistructured data, classification, summarization|
|Subjects:||Computer Science > Semistructured Data|
|Related URLs:||Project Homepage||http://infolab.stanford.edu/midas/midas.html|
|Deposited By:||Import Account|
|Deposited On:||25 Feb 2000 16:00|
|Last Modified:||01 Jan 2009 12:29|
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