Title
Izvođenje zakonitosti iz ekonomskih podataka primenom data mining pristupa
Creator
Milanović, Marina B. 1967-
Copyright date
2018
Object Links
Select license
Autorstvo-Nekomercijalno-Bez prerade 3.0 Srbija (CC BY-NC-ND 3.0)
License description
Dozvoljavate samo preuzimanje i distribuciju dela, ako/dok se pravilno naznačava ime autora, bez ikakvih promena dela i bez prava komercijalnog korišćenja dela. Ova licenca je najstroža CC licenca. Osnovni opis Licence: http://creativecommons.org/licenses/by-nc-nd/3.0/rs/deed.sr_LATN. Sadržaj ugovora u celini: http://creativecommons.org/licenses/by-nc-nd/3.0/rs/legalcode.sr-Latn
Language
Serbian
Cobiss-ID
Theses Type
Doktorska disertacija
description
Datum odbrane: 15.01.2019.
Other responsibilities
mentor
Lepojević, Vinko 1966-
član komisije
Đorđević, Vera
član komisije
Kalinić, Zoran 1971-
Academic Expertise
Društveno-humanističke nauke
University
Univerzitet u Nišu
Faculty
Ekonomski fakultet
Group
Katedra za računovodstvo, matematiku i informatiku
Alternative title
Extraction of regularities from economic data using data mining approach
Publisher
[М. B. Мilanović]
Format
300 listova
description
Biografija autora: list [304];
Bibliografija: listovi 289-300.
description
Statistics
Abstract (en)
The development of information technology and, consequently, rapid increase of the available amount of data have contributed to the fact that data mining, as a key component of a wider interactive, iterative and creative process of knowledge discovery from data, is of great importance in economic research. The basic idea of data mining is reflected in the efficient and effective identification of regularities, that are hidden in large sets of (multidimensional) data stored in information repositories, using software-supported methods and algorithms. Taking into account the foregoing, in this doctoral dissertation, the most important theoretical-methodological aspects of data mining approaches in data analysis are examined, as well as its applicative possibilities in the field of studying economic phenomena. In this sense, trends in the modern economy, from the perspective of the growing role of data (as a usable resource for generating values), fundamental terminology related to the concept of data mining as well as the positive and negative contexts of its application, have been analyzed. The tasks of discovering knowledge from data, in function of creating a data mining model, are viewed through the prism of a wide range of methodological procedures for their implementation. Special attention has been dedicated to the relationship between data mining and statistics, as a science that traditionally deals with the discovery of regularities from data.
The results of the research indicate the great potential of integrated implementation of statistical and data mining approaches in finding innovative methodological solutions to specific problems and, at the same time, suggest the need for mutual adaptation and modification of basic paradigms of data analysis on both sides. Empirical part of the dissertation points out innovative conceptually-methodological frameworks for analyzing data from time series of stock exchange indices and survey data on service users. Empirical results, as the exact knowledge extracted from data, confirm the importance of implementing data mining analysis in the problem contexts of economics, business economics and management. The conducted research represents a suitable basis for profiling future research orientations in the field of data mining application concerning the study of economic phenomena.
Authors Key words
Ekonomski podaci, znanje, zakonitosti, data mining, statistika
Authors Key words
economic data, knowledge, regularities, data mining, statistics
Classification
330:519.21/25:004.6(043.3)
Subject
S180
Type
Tekst
Abstract (en)
The development of information technology and, consequently, rapid increase of the available amount of data have contributed to the fact that data mining, as a key component of a wider interactive, iterative and creative process of knowledge discovery from data, is of great importance in economic research. The basic idea of data mining is reflected in the efficient and effective identification of regularities, that are hidden in large sets of (multidimensional) data stored in information repositories, using software-supported methods and algorithms. Taking into account the foregoing, in this doctoral dissertation, the most important theoretical-methodological aspects of data mining approaches in data analysis are examined, as well as its applicative possibilities in the field of studying economic phenomena. In this sense, trends in the modern economy, from the perspective of the growing role of data (as a usable resource for generating values), fundamental terminology related to the concept of data mining as well as the positive and negative contexts of its application, have been analyzed. The tasks of discovering knowledge from data, in function of creating a data mining model, are viewed through the prism of a wide range of methodological procedures for their implementation. Special attention has been dedicated to the relationship between data mining and statistics, as a science that traditionally deals with the discovery of regularities from data.
The results of the research indicate the great potential of integrated implementation of statistical and data mining approaches in finding innovative methodological solutions to specific problems and, at the same time, suggest the need for mutual adaptation and modification of basic paradigms of data analysis on both sides. Empirical part of the dissertation points out innovative conceptually-methodological frameworks for analyzing data from time series of stock exchange indices and survey data on service users. Empirical results, as the exact knowledge extracted from data, confirm the importance of implementing data mining analysis in the problem contexts of economics, business economics and management. The conducted research represents a suitable basis for profiling future research orientations in the field of data mining application concerning the study of economic phenomena.
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