By Nils Klarlund, Thomas Schwentick (auth.), Jan Chomicki, Ron van der Meyden, Gunter Saake (eds.)
In this period of heterogeneous and allotted info assets, starting from semistructured files to wisdom approximately coordination methods or workflows, good judgment presents a wealthy set of instruments and methods with which to deal with the questions of ways to symbolize, question and cause approximately complicated data.
This publication presents a cutting-edge assessment of study at the program of logic-based how to info structures, overlaying hugely topical and rising fields protecting XML programming and querying, clever brokers, workflow modeling and verification, information integration, temporal and dynamic info, info mining, authorization, and safeguard. It offers either scientists and graduate scholars with a wealth of fabric and references for his or her personal examine and education.
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It doesn't matter what DBMS you're using—Oracle, DB2, SQL Server, MySQL, PostgreSQL—misunderstandings can constantly come up over the correct meanings of phrases, misunderstandings which can have a significant impression at the good fortune of your database tasks. for instance, listed below are a few universal database phrases: characteristic, BCNF, consistency, denormalization, predicate, repeating workforce, subscribe to dependency.
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The program in the example above acts like one recursive function that is called on each node in the tree. In XSLT, we can simulate multiple, mutually recursive functions, using modes. A mode is a name given to a template rule, and all template rules having the same mode form one function. The example below illustrates this with a program that changes em to bf, but only directly under instruction, and that leaves all other em unchanged.
Monadic datalog and the expressive power of languages for web information extraction. In Proceedings of the 21st ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Madison, Wisconsin, June 2002. 46. G. Gottlob and C. Koch. Monadic queries over tree-structured data. In 17th Annual IEEE Symposium on Logic in Computer Science, 2002. 47. A. Le Hors et al. Document Object Model (DaM) level 3 Core Specification, W3C Working Draft 09 April 2002. Technical report, W3C, 2002. org/TR/2002/WD-DOM-Level-3-Core-20020409/.
6 27 XML Query Languages versus Automata and Logic Languages for querying and transforming XML trees are critical to applications such as XML data exchange and native XML data processing. In data exchange, we often need to transform an XML document that conforms to one schema into another document, containing essentially the same information but represented according to a different schema. This is needed, for example, when XML data crosses organizational boundaries. The core of a native XML engine consists of a query processor, which needs to optimize and execute queries over the XML data, much like a relational database query processor.