dc.contributor.author | Islam, Md Saiful | |
dc.contributor.author | Rahayu, Wenny | |
dc.contributor.author | Liu, Chengfei | |
dc.contributor.author | Anwar, Tarique | |
dc.contributor.author | Stantic, Bela | |
dc.contributor.editor | Bin Dong | |
dc.date.accessioned | 2017-10-26T01:31:28Z | |
dc.date.available | 2017-10-26T01:31:28Z | |
dc.date.issued | 2017 | |
dc.identifier.isbn | 9781450352826 | |
dc.identifier.doi | 10.1145/3085504.3085508 | |
dc.identifier.uri | http://hdl.handle.net/10072/346294 | |
dc.description.abstract | Understanding 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.peerreviewed | Yes | |
dc.language | English | |
dc.publisher | Association for Computing Machinery (ACM) | |
dc.publisher.place | United States | |
dc.relation.ispartofconferencename | 29th International Conference on Scientifc and Statistical Database Management (SSDBM) | |
dc.relation.ispartofconferencetitle | SSDBM 2017: 29TH INTERNATIONAL CONFERENCE ON SCIENTIFIC AND STATISTICAL DATABASE MANAGEMENT | |
dc.relation.ispartofdatefrom | 2017-06-27 | |
dc.relation.ispartofdateto | 2017-06-29 | |
dc.relation.ispartoflocation | Chicago, IL | |
dc.relation.ispartofpagefrom | 12 pages | |
dc.relation.ispartofpageto | 12 pages | |
dc.relation.ispartofvolume | Part F128636 | |
dc.subject.fieldofresearch | Data management and data science not elsewhere classified | |
dc.subject.fieldofresearch | Data structures and algorithms | |
dc.subject.fieldofresearch | Query processing and optimisation | |
dc.subject.fieldofresearchcode | 460599 | |
dc.subject.fieldofresearchcode | 461305 | |
dc.subject.fieldofresearchcode | 460509 | |
dc.title | Computing influence of a product through uncertain reverse skyline | |
dc.type | Conference output | |
dc.type.description | E1 - Conferences | |
dc.type.code | E - Conference Publications | |
dc.description.version | Accepted Manuscript (AM) | |
gro.faculty | Griffith 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.hasfulltext | Full Text | |
gro.griffith.author | Stantic, Bela | |