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dc.contributor.author Braun, Peter
dc.contributor.author Cuzzocrea, Alfredo
dc.contributor.author Leung, Carson
dc.contributor.author Pazdor, Adam G.M.
dc.contributor.author Souza, Joglas
dc.date.accessioned 2019-01-08T18:34:49Z
dc.date.available 2019-01-08T18:34:49Z
dc.date.issued 2018
dc.date.submitted 2019-01-08T07:56:29Z en
dc.identifier.citation P. Braun, A. Cuzzocrea, C.K. Leung, A.G.M. Pazdor, J. Souza. Item-centric mining of frequent patterns from big uncertain data. Procedia Computer Science, 126 (2018), pp. 1875-1884 en_US
dc.identifier.uri http://hdl.handle.net/1993/33659
dc.description.abstract High volumes of wide varieties of valuable data of different veracity (e.g., imprecise and uncertain data) can be easily generated or collected at a high velocity for various knowledge-based and intelligent information & engineering systems in many real-life situations. Embedded in these big data is valuable knowledge and useful information, which can be discovered by data science solutions. As a popular data science task, frequent pattern mining aims to discover implicit, previously unknown and potentially useful information and valuable knowledge in terms of sets of frequently co-occurring items. Many of the existing frequent pattern mining algorithms use a transaction-centric mining approach to find frequent patterns from precise data. However, there are situations in which an item-centric mining approach is more appropriate, and there are also situations in which data are imprecise and uncertain. In this article, we present an item-centric algorithm for mining frequent patterns from big uncertain data. Evaluation results show the effectiveness of our algorithm in item-centric mining of frequent patterns from big uncertain data. en_US
dc.description.sponsorship Natural Sciences and Engineering Research Council of Canada (NSERC); University of Manitoba en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.rights info:eu-repo/semantics/openAccess
dc.subject big data en_US
dc.subject data analytics en_US
dc.subject data mining en_US
dc.subject data science en_US
dc.subject frequent patterns en_US
dc.subject imprecise data en_US
dc.subject uncertain data en_US
dc.subject knowledge discovery in databases en_US
dc.subject uncertainty en_US
dc.subject vertical mining en_US
dc.title Item-centric mining of frequent patterns from big uncertain data en_US
dc.type Article en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1016/j.procs.2018.08.075


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