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dc.contributor.authorIslam, Md Saiful
dc.contributor.authorRahayu, Wenny
dc.contributor.authorLiu, Chengfei
dc.contributor.authorAnwar, Tarique
dc.contributor.authorStantic, Bela
dc.contributor.editorBin Dong
dc.date.accessioned2017-10-26T01:31:28Z
dc.date.available2017-10-26T01:31:28Z
dc.date.issued2017
dc.identifier.isbn9781450352826
dc.identifier.doi10.1145/3085504.3085508
dc.identifier.urihttp://hdl.handle.net/10072/346294
dc.description.abstractUnderstanding the influence of a product is crucially important for making informed business decisions. This paper introduces a new type of skyline queries, called uncertain reverse skyline, for measuring the influence of a probabilistic product in uncertain data settings. More specifically, given a dataset of probabilistic products P and a set of customers C, an uncertain reverse skyline of a probabilistic product q retrieves all customers c ∈ C which include q as one of their preferred products. We present efficient pruning ideas and techniques for processing the uncertain reverse skyline query of a probabilistic product using R-Tree data index. We also present an efficient parallel approach to compute the uncertain reverse skyline and influence score of a probabilistic product. Our approach significantly outperforms the baseline approach derived from the existing literature. The efficiency of our approach is demonstrated by conducting experiments with both real and synthetic datasets.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherAssociation for Computing Machinery (ACM)
dc.publisher.placeUnited States
dc.relation.ispartofconferencename29th International Conference on Scientifc and Statistical Database Management (SSDBM)
dc.relation.ispartofconferencetitleSSDBM 2017: 29TH INTERNATIONAL CONFERENCE ON SCIENTIFIC AND STATISTICAL DATABASE MANAGEMENT
dc.relation.ispartofdatefrom2017-06-27
dc.relation.ispartofdateto2017-06-29
dc.relation.ispartoflocationChicago, IL
dc.relation.ispartofpagefrom12 pages
dc.relation.ispartofpageto12 pages
dc.relation.ispartofvolumePart F128636
dc.subject.fieldofresearchData management and data science not elsewhere classified
dc.subject.fieldofresearchData structures and algorithms
dc.subject.fieldofresearchQuery processing and optimisation
dc.subject.fieldofresearchcode460599
dc.subject.fieldofresearchcode461305
dc.subject.fieldofresearchcode460509
dc.titleComputing influence of a product through uncertain reverse skyline
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionAccepted Manuscript (AM)
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© ACM 2017. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 29th International Conference on Scientific and Statistical Database Management, ISBN: 978-1-4503-5282-6, 10.1145/3085504.3085508.
gro.hasfulltextFull Text
gro.griffith.authorStantic, Bela


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