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https://doi.org/10.17559/TV-20171109130510

Improved Visualization of Frequent Itemset Relationships Using the Minimal Spanning Tree Algorithm

Mihaela Vranić ; FER, University of Zagreb, Unska 3, 10000 Zagreb, Croatia
Damir Pintar   ORCID icon orcid.org/0000-0001-9589-7890 ; FER, University of Zagreb, Unska 3, 10000 Zagreb, Croatia
Frano Škopljanac-Mačina ; FER, University of Zagreb, Unska 3, 10000 Zagreb, Croatia

Puni tekst: engleski, pdf (1 MB) str. 331-338 preuzimanja: 364* citiraj
APA 6th Edition
Vranić, M., Pintar, D. i Škopljanac-Mačina, F. (2019). Improved Visualization of Frequent Itemset Relationships Using the Minimal Spanning Tree Algorithm. Tehnički vjesnik, 26 (2), 331-338. https://doi.org/10.17559/TV-20171109130510
MLA 8th Edition
Vranić, Mihaela, et al. "Improved Visualization of Frequent Itemset Relationships Using the Minimal Spanning Tree Algorithm." Tehnički vjesnik, vol. 26, br. 2, 2019, str. 331-338. https://doi.org/10.17559/TV-20171109130510. Citirano 12.05.2021.
Chicago 17th Edition
Vranić, Mihaela, Damir Pintar i Frano Škopljanac-Mačina. "Improved Visualization of Frequent Itemset Relationships Using the Minimal Spanning Tree Algorithm." Tehnički vjesnik 26, br. 2 (2019): 331-338. https://doi.org/10.17559/TV-20171109130510
Harvard
Vranić, M., Pintar, D., i Škopljanac-Mačina, F. (2019). 'Improved Visualization of Frequent Itemset Relationships Using the Minimal Spanning Tree Algorithm', Tehnički vjesnik, 26(2), str. 331-338. https://doi.org/10.17559/TV-20171109130510
Vancouver
Vranić M, Pintar D, Škopljanac-Mačina F. Improved Visualization of Frequent Itemset Relationships Using the Minimal Spanning Tree Algorithm. Tehnički vjesnik [Internet]. 2019 [pristupljeno 12.05.2021.];26(2):331-338. https://doi.org/10.17559/TV-20171109130510
IEEE
M. Vranić, D. Pintar i F. Škopljanac-Mačina, "Improved Visualization of Frequent Itemset Relationships Using the Minimal Spanning Tree Algorithm", Tehnički vjesnik, vol.26, br. 2, str. 331-338, 2019. [Online]. https://doi.org/10.17559/TV-20171109130510

Sažetak
Descriptive data mining techniques offer a way of extracting useful information out of large datasets and presenting it in an interpretable fashion to be used as a basis for future decisions. Since users interpret information most easily through visual means, techniques which produce concise, visually attractive results are usually preferred. We define a method, which converts transactional data into tree-like data structures, which depict important relationships between items contained in this data. The new approach we propose is offering a way to mitigate the loss of information present in previously developed algorithms, which use mined frequent itemsets and construct tree structures. We transfer the problem to the domain of graph theory and through minimal spanning tree construction achieve more informative visualizations. We highlight the new approach with comparison to previous ones by applying it on a real-life datasets – one connected to market basket data and the other from the educational domain.

Ključne riječi
association rules; data mining; dendrograms; frequent itemsets; minimal spanning tree; transactional data; visual representation

Hrčak ID: 219508

URI
https://hrcak.srce.hr/219508

Posjeta: 602 *