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Izvorni znanstveni članak
https://doi.org/10.17535/crorr.2015.0036

Discovering market basket patterns using hierarchical association rules

Marijana Zekić-Sušac ; Faculty of Economics in Osijek, University of Josip Juraj Strossmayer in Osijek, Osijek, Croatia
Adela Has ; Faculty of Economics in Osijek, University of Josip Juraj Strossmayer in Osijek, Osijek, Croatia

Puni tekst: engleski, pdf (276 KB) str. 475-487 preuzimanja: 662* citiraj
APA 6th Edition
Zekić-Sušac, M. i Has, A. (2015). Discovering market basket patterns using hierarchical association rules. Croatian Operational Research Review, 6 (2), 475-487. https://doi.org/10.17535/crorr.2015.0036
MLA 8th Edition
Zekić-Sušac, Marijana i Adela Has. "Discovering market basket patterns using hierarchical association rules." Croatian Operational Research Review, vol. 6, br. 2, 2015, str. 475-487. https://doi.org/10.17535/crorr.2015.0036. Citirano 17.06.2019.
Chicago 17th Edition
Zekić-Sušac, Marijana i Adela Has. "Discovering market basket patterns using hierarchical association rules." Croatian Operational Research Review 6, br. 2 (2015): 475-487. https://doi.org/10.17535/crorr.2015.0036
Harvard
Zekić-Sušac, M., i Has, A. (2015). 'Discovering market basket patterns using hierarchical association rules', Croatian Operational Research Review, 6(2), str. 475-487. doi: https://doi.org/10.17535/crorr.2015.0036
Vancouver
Zekić-Sušac M, Has A. Discovering market basket patterns using hierarchical association rules. Croatian Operational Research Review [Internet]. 2015 [pristupljeno 17.06.2019.];6(2):475-487. doi: https://doi.org/10.17535/crorr.2015.0036
IEEE
M. Zekić-Sušac i A. Has, "Discovering market basket patterns using hierarchical association rules", Croatian Operational Research Review, vol.6, br. 2, str. 475-487, 2015. [Online]. doi: https://doi.org/10.17535/crorr.2015.0036

Sažetak
Association rules are a data mining method for discovering patterns of frequent item sets, such as products in a store that are frequently purchased at the same time by a customer (market basket analysis). A number of interestingness measures for association rules have been developed to date, but research has shown that there a dominant measure does not exist. Authors have mostly used objective measures, whereas subjective measures have rarely been investigated. This paper aims to combine objective measures such as support, confidence and lift with a subjective approach based on human expert selection in order to extract interesting rules from a real dataset collected from a large Croatian retail chain. Hierarchical association rules were used to enhance the efficiency of the extraction rule. The results show that rules that are more interesting were extracted using the hierarchical method, and that a hybrid approach of combining objective and subjective measures succeeds in extracting certain unexpected and actionable rules. The research can be useful for retail and marketing managers in planning marketing strategies, as well as for researchers investigating this field.

Ključne riječi
association rules; data mining; market basket analysis

Hrčak ID: 148275

URI
https://hrcak.srce.hr/148275

Posjeta: 927 *