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dc.contributor.authorRudra, Amit
dc.contributor.authorGopalan, Raj
dc.contributor.authorAchuthan, Narasimaha
dc.contributor.editorSalimane Hammoudi, Leszek Maciaszek, Jose Cordeiro and Jan Dietz
dc.date.accessioned2017-01-30T13:38:07Z
dc.date.available2017-01-30T13:38:07Z
dc.date.created2013-09-09T20:00:36Z
dc.date.issued2013
dc.identifier.citationRudra, Amit and Gopalan, Raj and Achuthan, Narasimaha. 2013. Selecting adequate samples for approximate decision support queries, in Hammoudi, S. and Maciaszek, L. and Cordeiro. J. and Dietz, J. (ed), ICEIS 2013, Jul 4-7 2013, pp. 46-55. Angers, France: Science and Technology Publications.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/33606
dc.description.abstract

For highly selective queries, a simple random sample of records drawn from a large data warehouse may not contain sufficient number of records that satisfy the query conditions. Efficient sampling schemes for such queries require innovative techniques that can access records that are relevant to each specific query. In drawing the sample, it is advantageous to know what would be an adequate sample size for a given query. This paper proposes methods for picking adequate samples that ensure approximate query results with a desired level of accuracy. A special index based on a structure known as the k-MDI Tree is used to draw samples. An unbiased estimator named inverse simple random sampling without replacement is adapted to estimate adequate sample sizes for queries. The methods are evaluated experimentally on a large real life data set. The results of evaluation show that adequate sample sizes can be determined such that errors in outputs of most queries are wtihin the acceptable limit of 5%.

dc.publisherScience and Technology Publications
dc.subjectData Warehousing
dc.subjectInverse Simple Random Sample without Replacement (SRSWOR)
dc.subjectApproximate Query Processing
dc.subjectSampling
dc.titleSelecting adequate samples for approximate decision support queries
dc.typeConference Paper
dcterms.source.startPage46
dcterms.source.endPage55
dcterms.source.titleProceedings of the 15th International Conference on Enterprise Information Systems
dcterms.source.seriesProceedings of the 15th International Conference on Enterprise Information Systems
dcterms.source.isbn9789898565594
dcterms.source.conferenceICEIS 2013
dcterms.source.conference-start-dateJul 4 2013
dcterms.source.conferencelocationAngers, France
dcterms.source.placeFrance
curtin.department
curtin.accessStatusOpen access


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