Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-40285-2_10
Title: Discovering semantics from data-centric XML
Authors: Li, L.
Le, T.N.
Wu, H.
Ling, T.W. 
Bressan, S. 
Issue Date: 2013
Source: Li, L.,Le, T.N.,Wu, H.,Ling, T.W.,Bressan, S. (2013). Discovering semantics from data-centric XML. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8055 LNCS (PART 1) : 88-102. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-40285-2_10
Abstract: In database applications, the availability of a conceptual schema and semantics constitute invaluable leverage for improving the effectiveness, and sometimes the efficiency, of many tasks including query processing, keyword search and schema/data integration. The Object-Relationship-Attribute model for Semi-Structured data (ORA-SS) model is a conceptual model intended to capture the semantics of object classes, object identifiers, relationship types, etc., underlying XML schemas and data. We refer to the set of these semantic concepts as the ORA-semantics. In this work, we present a novel approach to automatically discover the ORA-semantics from data-centric XML. We also empirically and comparatively evaluate the effectiveness of the approach. © 2013 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/78098
ISBN: 9783642402845
ISSN: 03029743
DOI: 10.1007/978-3-642-40285-2_10
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