A Research Survey on Large XML Data: Streaming, Selectivity Estimation and Parallelism

Abstract : Semi-structured data sets in the form of XML documents have many practical uses and they have motivated a very large amount of work in theoretical, applied and industrial computing. Their efficient exploitation requires specific methods for filtering and querying them, using techniques that are neither keyword searches nor relational methods. In this paper we survey a large body of recent research on efficient querying methods for XML data. Our analysis of the literature follows the three dimensions of stream-processing, parallel processing and performance variability.
Type de document :
Chapitre d'ouvrage
F. Xhafa and N. Bessis. Inter-cooperative Collective Intelligence: Techniques and Applications, Springer, 2013, ISBN 978-3-642-35015-3
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https://hal.inria.fr/hal-00823325
Contributeur : Gaétan Hains <>
Soumis le : jeudi 16 mai 2013 - 16:06:45
Dernière modification le : jeudi 11 janvier 2018 - 06:19:28

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  • HAL Id : hal-00823325, version 1

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Muath Alrammal, Gaétan Hains. A Research Survey on Large XML Data: Streaming, Selectivity Estimation and Parallelism. F. Xhafa and N. Bessis. Inter-cooperative Collective Intelligence: Techniques and Applications, Springer, 2013, ISBN 978-3-642-35015-3. 〈hal-00823325〉

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