Improved Visualization of Frequent Itemset Relationships Using the Minimal Spanning Tree Algorithm (CROSBI ID 265875)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Vranić, Mihaela ; Pintar, Damir ; Škopljanac- Mačina, Frano
engleski
Improved Visualization of Frequent Itemset Relationships Using the Minimal Spanning Tree Algorithm
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.
association rules ; data mining ; dendrograms ; frequent itemsets ; minimal spanning tree ; transactional data ; visual representation
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Podaci o izdanju
26 (2)
2019.
331-338
objavljeno
1330-3651
1848-6339
10.17559/tv-20171109130510
Povezanost rada
Elektrotehnika, Računarstvo