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Distributed data mining systems: Techniques, approaches and algorithms

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dc.title Distributed data mining systems: Techniques, approaches and algorithms en
dc.contributor.author Ali, Ammar Alhaj
dc.contributor.author Vařacha, Pavel
dc.contributor.author Krayem, Said
dc.contributor.author Žáček, Petr
dc.contributor.author Urbanek, Andrzej
dc.relation.ispartof MATEC Web of Conferences
dc.identifier.issn 2261-236X Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2018
utb.relation.volume 210
dc.event.title 22nd International Conference on Circuits, Systems, Communications and Computers, CSCC 2018
dc.event.location Majorca
utb.event.state-en Spain
utb.event.state-cs Španělsko
dc.event.sdate 2018-07-14
dc.event.edate 2018-07-17
dc.type conferenceObject
dc.language.iso en
dc.publisher EDP Sciences
dc.identifier.doi 10.1051/matecconf/201821004038
dc.relation.uri https://www.matec-conferences.org/articles/matecconf/abs/2018/69/matecconf_cscc2018_04038/matecconf_cscc2018_04038.html
dc.description.abstract Nowadays, we are living in the midst of a data explosion and seeing a massive growth in databases so with the wide availability of huge amounts of data; necessarily we are become in need for turning this data into useful information and knowledge, where Data mining uncovers interesting patterns and relationships hidden in a large volume of raw data and big data is a new term used to identify the datasets that are of large size and have grater complexity. The knowledge gained from data can be used for applications such as market analysis, customer retention and production control. Data mining is a massive computing task that deals with huge amount of stored data in a centralized or distributed system to extract useful information or knowledge. In this paper, we will discuss Distributed Data Mining systems, approaches, Techniques and algorithms to deal with distributed data to discover knowledge from distributed data in an effective and efficient way. © 2018 The Authors, published by EDP Sciences. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1008344
utb.identifier.obdid 43879538
utb.identifier.scopus 2-s2.0-85055584899
utb.identifier.wok 000567668400115
utb.source d-scopus
dc.date.accessioned 2019-01-03T12:31:47Z
dc.date.available 2019-01-03T12:31:47Z
dc.description.sponsorship Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; IGA (Internal Grant Agency) of Tomas Bata University in Zlin [IGA/CebiaTech/2017/007]
utb.contributor.internalauthor Ali, Ammar Alhaj
utb.contributor.internalauthor Vařacha, Pavel
utb.contributor.internalauthor Krayem, Said
utb.contributor.internalauthor Žáček, Petr
utb.wos.affiliation [Ali, Ammar Alhaj; Varacha, Pavel; Krayem, Said; Zacek, Petr] Tomas Bata Univ Zlin, Fac Appl Informat, Zlin, Czech Republic; [Urbanek, Andrzej] Pomorska Acad Slupsk, Slupsk, Poland
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlin, Czech Republic; Pomorska Academia in Slupsk, Poland
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