NDLI: Discovering XSD keys from XML data

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Discovering XSD keys from XML data

Content Provider	ACM Digital Library
Author	Van den Bussche, Jan Neven, Frank Ugarte, Martin Vansummeren, Stijn Arenas, Marcelo Daenen, Jonny
Abstract	A great deal of research into the learning of schemas from XML data has been conducted in recent years to enable the automatic discovery of XML Schemas from XML documents when no schema, or only a low-quality one is available. Unfortunately, and in strong contrast to, for instance, the relational model, the automatic discovery of even the simplest of XML constraints, namely XML keys, has been left largely unexplored in this context. A major obstacle here is the unavailability of a theory on reasoning about XML keys in the presence of XML schemas, which is needed to validate the quality of candidate keys. The present paper embarks on a fundamental study of such a theory and classifies the complexity of several crucial properties concerning XML keys in the presence of an XSD, like, for instance, testing for consistency, boundedness, satisfiability, universality, and equivalence. Of independent interest, novel results are obtained related to cardinality estimation of XPath result sets. A mining algorithm is then developed within the framework of levelwise search. The algorithm leverages known discovery algorithms for functional dependencies in the relational model, but incorporates the above mentioned properties to assess and refine the quality of derived keys. An experimental study on an extensive body of real world XML data evaluating the effectiveness of the proposed algorithm is provided.
Starting Page	61
Ending Page	72
Page Count	12
File Format	PDF
ISBN	9781450320375
DOI	10.1145/2463676.2463705
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-06-22
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Mining Xml Key
Content Type	Text
Resource Type	Article

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