Pregled bibliografske jedinice broj: 701637
Data Mining Applications Framework for Business Organizations: Business Functions Approach
Data Mining Applications Framework for Business Organizations: Business Functions Approach // The Business Review, Cambridge / Tubbs, Stewart L. ; Scannell, N. ; Demirdjian, Z.S ; Guo, K.L. ; Arbogast, G.W. ; Ng, L. ; Pinar, M. ; Steinbuch, P. ; Santora, J.C. ; Ozenbas, D. ; Flint, D. ; Schultz, M.C. ; Parks, R.H. ; Maniam, B. ; Wright, D. ; Rapp, W.V. ; Werner, M. ; Fuller, J.A. ; Locke, S. ; Hanagriff, R.D. ; Senguder, T. (ur.).
Honolulu (HI), Sjedinjene Američke Države, 2014. str. 119-126 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Data Mining Applications Framework for Business Organizations: Business Functions Approach
Autori
Zoroja, Jovana ; Pejic Bach, Mirjana ; Ćurko, Katarina
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
The Business Review, Cambridge
/ Tubbs, Stewart L. ; Scannell, N. ; Demirdjian, Z.S ; Guo, K.L. ; Arbogast, G.W. ; Ng, L. ; Pinar, M. ; Steinbuch, P. ; Santora, J.C. ; Ozenbas, D. ; Flint, D. ; Schultz, M.C. ; Parks, R.H. ; Maniam, B. ; Wright, D. ; Rapp, W.V. ; Werner, M. ; Fuller, J.A. ; Locke, S. ; Hanagriff, R.D. ; Senguder, T. - , 2014, 119-126
Skup
The Economics, Finance, Accounting & Management Research Conference, Hawaii
Mjesto i datum
Honolulu (HI), Sjedinjene Američke Države, 29.05.2014. - 01.06.2014
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
data mining techniques; business organizations; review; data mining applications
Sažetak
High growth of data in databases created a need for technologies which can extract and uncover the hidden information in large amount of data which can be useful in decision making in business organizations. Data mining is a technology that could solve this problem with approach combining machine learning, statistics and database management that are used for finding useful and valid patterns in data. The goal of this paper is to present a review of published data mining applications in business organizations across business functions. Papers from the journals indexed in Web of Science that investigate data mining applications in business organizations were examined in order to compare the research on data mining applications in terms of: (1) journal, (2) title of the paper, (3) data collection approach, (4) methodology used for investigation of data mining applications and (5) keywords. We investigated 25 papers divided into five categories: finance, human resources, transport, marketing and sales and services. We found research papers for each mentioned category. By random choice method we have selected several research papers for each category in order to compare data mining applications, methods and data used in business organizations.
Izvorni jezik
Engleski
Znanstvena područja
Ekonomija, Informacijske i komunikacijske znanosti
POVEZANOST RADA
Ustanove:
Ekonomski fakultet, Zagreb
