Hybrid Fragmentation of XML Data Warehouse Using K-Means Algorithm

Autor:	Safia Nait Bahloul, Mohamed Kechar
Rok vydání:	2014
Předmět:	Xml data Computer science computer.internet_protocol Fragmentation (computing) k-means clustering Data mining computer.software_genre computer XML Oracle Warehouse XPath
Zdroj:	Advances in Databases and Information Systems ISBN: 9783319109329 ADBIS
DOI:	10.1007/978-3-319-10933-6_6
Popis:	The efficiency of the decision-making process in an XML data warehouse environment, is in a narrow relation with the performances of decision-support queries. Optimize these performances, automatically contribute in improving decision making. One of the important performances optimization techniques in XML data warehouse is fragmentation with its different variants (horizontal fragmentation and vertical fragmentation). In this paper, we develop a hybrid fragmentation algorithm combining a vertical fragmentation based on XPath expressions and a horizontal fragmentation based on selection predicates. To control the number of fragments, we use the K-Means algorithm. Finally, we validate our approach under Oracle Berkeley DB XML by several experiments done on XML data, derived from the XWB benchmark.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d20061c40862a7b741378578ffdff5ff https://doi.org/10.1007/978-3-319-10933-6_6 Zobrazit plný text záznamu