Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/39711
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dc.titleBuilding XML data warehouse based on frequent patterns in user queries
dc.contributor.authorZhang, J.
dc.contributor.authorLing, T.W.
dc.contributor.authorBruckner, R.M.
dc.contributor.authorTjoa, A.M.
dc.date.accessioned2013-07-04T07:47:50Z
dc.date.available2013-07-04T07:47:50Z
dc.date.issued2003
dc.identifier.citationZhang, J.,Ling, T.W.,Bruckner, R.M.,Tjoa, A.M. (2003). Building XML data warehouse based on frequent patterns in user queries. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2737 : 99-108. ScholarBank@NUS Repository.
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39711
dc.description.abstractWith the proliferation of XML-based data sources available across the Internet, it is increasingly important to provide users with a data warehouse of XML data sources to facilitate decision-making processes. Due to the extremely large amount of XML data available on web, unguided warehousing of XML data turns out to be highly costly and usually cannot well accommodate the users' needs in XML data acquirement. In this paper, we propose an approach to materialize XML data warehouses based on frequent query patterns discovered from historical queries issued by users. The schemas of integrated XML documents in the warehouse are built using these frequent query patterns represented as Frequent Query Pattern Trees (FreqQPTs). Using hierarchical clustering technique, the integration approach in the data warehouse is flexible with respect to obtaining and maintaining XML documents. Experiments show that the overall processing of the same queries issued against the global schema become much efficient by using the XML data warehouse built than by directly searching the multiple data sources. © Springer-Verlag Berlin Heidelberg 2003.
dc.sourceScopus
dc.typeArticle
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.volume2737
dc.description.page99-108
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

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