Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/42329
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dc.titleAutomatic generation of XQuery view definitions from ORA-SS views
dc.contributor.authorChen, Y.B.
dc.contributor.authorLing, T.W.
dc.contributor.authorLee, M.L.
dc.date.accessioned2013-07-04T08:49:04Z
dc.date.available2013-07-04T08:49:04Z
dc.date.issued2003
dc.identifier.citationChen, Y.B.,Ling, T.W.,Lee, M.L. (2003). Automatic generation of XQuery view definitions from ORA-SS views. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2813 : 158-171. ScholarBank@NUS Repository.
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/42329
dc.description.abstractMany Internet-based applications have adopted XML as the standard data exchange format. These XML data are typically stored in its native form, thus creating the need to present XML views over the underlying data files, and to allow users to query these views. Using a conceptual model for the design and querying of XML views provides a fast and user-friendly approach to retrieve XML data. The Object-Relationship-Attribute model for SemiStructured data (ORA-SS) is a semantically rich model that facilitates the design of valid XML views. It preserves semantic information in the source data. In this paper, we develop a method that automatically generates view definitions in XQuery from views that have been designed using the ORA-SS model. This technique can be used to materialize the views and map queries issued on XML views into the equivalent queries in XQuery syntax on the source XML data. This removes the need for users to manually write XQuery expressions. An analysis of the correctness of the proposed algorithm is also given. © Springer-Verlag Berlin Heidelberg 2003.
dc.sourceScopus
dc.typeReview
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume2813
dc.description.page158-171
dc.identifier.isiutNOT_IN_WOS
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