DIRA: A Framework Of Data Integration Using Data Quality

dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorI Abdel Monem, Reham
dc.contributor.authorH El-Bastawissy, Ali
dc.contributor.authorM Elwakil, Mohamed
dc.date.accessioned2020-02-03T07:19:22Z
dc.date.available2020-02-03T07:19:22Z
dc.date.issued2016
dc.descriptionMSA Google Scholaren_US
dc.description.abstractData integration is the process of collecting data from different data sources and providing user withunified view of answers that meet his requirements. The quality of query answers can be improved by identifying the quality of data sources according to some quality measures and retrieving data from only significant ones. Query answers that returned from significant data sources can be ranked according toquality requirements that specified in user query and proposed queries types to return only top-k query answers. In this paper, Data integration framework called Data integration to return ranked alternatives (DIRA) will be introduced depending on data quality assessment module that will use data sources quality to choose the significant ones and ranking algorithm to return top-k query answers according to different queries types.en_US
dc.description.sponsorshiparXiv preprinten_US
dc.identifier.issn2230-9608
dc.identifier.urihttps://cutt.ly/erI9vq1
dc.language.isoenen_US
dc.publisherarXiv preprinten_US
dc.relation.ispartofseriesarXiv preprint;
dc.subjectOctober University for University for Data integrationen_US
dc.subjectdata sourcesen_US
dc.subjectquery answersen_US
dc.subjectquality measuresen_US
dc.subjecttop-k query answersen_US
dc.subjectassessment moduleen_US
dc.subjectranking algorithmen_US
dc.titleDIRA: A Framework Of Data Integration Using Data Qualityen_US
dc.typeArticleen_US

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