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Original scientific paper

Software solutions in marketing research for knowledge discovery in databases by fuzzy clustering

Brano Markić
Dražena Tomić

Fulltext: english, pdf (612 KB) pages 240-244 downloads: 739* cite
APA 6th Edition
Markić, B. & Tomić, D. (2006). Software solutions in marketing research for knowledge discovery in databases by fuzzy clustering. Informatologia, 39 (4), 240-244. Retrieved from https://hrcak.srce.hr/9251
MLA 8th Edition
Markić, Brano and Dražena Tomić. "Software solutions in marketing research for knowledge discovery in databases by fuzzy clustering." Informatologia, vol. 39, no. 4, 2006, pp. 240-244. https://hrcak.srce.hr/9251. Accessed 15 Aug. 2020.
Chicago 17th Edition
Markić, Brano and Dražena Tomić. "Software solutions in marketing research for knowledge discovery in databases by fuzzy clustering." Informatologia 39, no. 4 (2006): 240-244. https://hrcak.srce.hr/9251
Harvard
Markić, B., and Tomić, D. (2006). 'Software solutions in marketing research for knowledge discovery in databases by fuzzy clustering', Informatologia, 39(4), pp. 240-244. Available at: https://hrcak.srce.hr/9251 (Accessed 15 August 2020)
Vancouver
Markić B, Tomić D. Software solutions in marketing research for knowledge discovery in databases by fuzzy clustering. Informatologia [Internet]. 2006 [cited 2020 August 15];39(4):240-244. Available from: https://hrcak.srce.hr/9251
IEEE
B. Markić and D. Tomić, "Software solutions in marketing research for knowledge discovery in databases by fuzzy clustering", Informatologia, vol.39, no. 4, pp. 240-244, 2006. [Online]. Available: https://hrcak.srce.hr/9251. [Accessed: 15 August 2020]

Abstracts
Knowledge discovery in databases is the process of identifying nove, valid, useful and ultimately understandable patterns in data stored in databases. Data mining is only a step in this process in charge to find patterns or models in data. There are many data mining algorithms for clustering. Clustering is unsupervised classification, the process of grouping the data into classes so that the data objects (examples) are similar to one and other within the same cluster and dissimilar to the objects in other clusters. In the paper is developed a conceptual model and program solution for clustering data stored in subject oriented data warehouse. Data warehouse and mining algorithms are integrated and this integration has shown satisfactory implementation power.

Keywords
knowledge discovery; data mining; data warehouse; cluster algorithms

Hrčak ID: 9251

URI
https://hrcak.srce.hr/9251

[croatian]

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