Data Mining-based Fragmentation of XML Data Warehouses

dc.creatorMahboubi, Hadj
dc.creatorDarmont, Jérôme
dc.date2008-11-05
dc.date.accessioned2026-07-07T10:15:42Z
dc.date.available2026-07-07T10:15:42Z
dc.descriptionWith the multiplication of XML data sources, many XML data warehouse models have been proposed to handle data heterogeneity and complexity in a way relational data warehouses fail to achieve. However, XML-native database systems currently suffer from limited performances, both in terms of manageable data volume and response time. Fragmentation helps address both these issues. Derived horizontal fragmentation is typically used in relational data warehouses and can definitely be adapted to the XML context. However, the number of fragments produced by classical algorithms is difficult to control. In this paper, we propose the use of a k-means-based fragmentation approach that allows to master the number of fragments through its $k$ parameter. We experimentally compare its efficiency to classical derived horizontal fragmentation algorithms adapted to XML data warehouses and show its superiority.
dc.identifierhttps://arxiv.org/abs/0811.0741
dc.identifierhttp://arxiv.org/abs/0811.0741
dc.identifierACM 11th International Workshop on Data Warehousing and OLAP (CIKM/DOLAP 08), Napa Valley : États-Unis d'Amérique (2008)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/173261
dc.subjectDatabases
dc.subjectH.2
dc.titleData Mining-based Fragmentation of XML Data Warehouses
dc.typetext

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