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Title:Podatkovno rudarjenje na področju spletne maloprodaje: študija primera specifične trgovine z darili v Veliki Britaniji : Diplomska naloga
Authors:ID Rukše, Leja (Author)
ID Boshkoska, Biljana Mileva (Mentor) More about this mentor... New window
Files:.pdf RAZ_Rukse_Leja_i2020.pdf (1,57 MB)
MD5: D6915766E5CF8E15933EF4BFB1CD5A18
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FIŠ - Faculty of Information Studies in Novo mesto
Abstract:V diplomskem delu je rdeča nit podatkovno rudarjenje. Gre za eno izmed tehnoloških rešitev, ki pomagajo v podjetjih in znanstvenih ustanovah pri odkrivanju znanja v kupu podatkov, ki jih imenujemo tudi Big Data. Gre za odkrivanje vzorcev in povezav, ki koristijo, gledano trgovska podjetja, pri opredeljevanju strank med zveste kupce, tiste, ki se pogosto poslužujejo nakupov ali so redki kupci, zapravijo v podjetju največ ali pa so pogosti kupci. Namen rudarjenja je iz analiz razbrati, kaj stranka potrebuje in katere stranke se bodo z večjo verjetnostjo odzvale na ponudbo. Sicer pa je bistveno pri podatkovnem rudarjenju tudi to, da se uporablja lahko v vseh panogah in znatno pripomore k lažjemu poslovanju. V drugem delu je v empiričnem delu pred-stavljena konkretna analiza razvrščanja v skupine z rezultati.
Keywords:podatkovno rudarjenje, Weka, analiza, atribut, filtriranje, razvrščanje v skupine, k-means
Place of publishing:Novo mesto
Place of performance:Novo mesto
Publisher:{L. Rukše}
Year of publishing:2020
Year of performance:2020
Number of pages:XIII, str. 59
PID:20.500.12556/ReVIS-6896 New window
COBISS.SI-ID:34009347 New window
UDC:004.8(043.2)
Note:Na ov.: Diplomska naloga : visokošolskega strokovnega študijskega programa prve stopnje;
Publication date in ReVIS:01.10.2020
Views:3099
Downloads:157
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:01.10.2020

Secondary language

Language:English
Abstract:The red thread of the thesis is data mining. It is one of the technilogical solutions that helps companies and scientific institutions in discovering knowledge in a pile of data, also called Big Data. It is about discovering patterns and connections with benefit, in the view of trading com-panies, identifying customers as loyal customers, those who make frequent purchases or are rare customers, spend the most in the company or are frequent customers. The purpose of mi-ning is to find out from the analyzes what the customer needs and which customers are more likely to respond to the offer. Otherwise, it is also essential in data mining that it can be used in all industries and significantly contributes to easier business. At the bottom, in the empirical part, a concrete analysis of clustering with results is presented.
Keywords:data mining, Weka, analysis, attribute, filtering, clustering, k-means


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