An Evolutionary Algorithm to Mine High-Utility Itemsets

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86094299" target="_blank" >RIV/61989100:27240/15:86094299 - isvavai.cz</a>
Result on the web
<a href="http://advances.utc.sk/index.php/AEEE/article/view/1474" target="_blank" >http://advances.utc.sk/index.php/AEEE/article/view/1474</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.15598/aeee.v13i4.1474" target="_blank" >10.15598/aeee.v13i4.1474</a>

Result language
angličtina
Original language name
An Evolutionary Algorithm to Mine High-Utility Itemsets
Original language description
High-utility itemset mining (HUIM) is a critical issue in recent years since it can be used to reveal the profitable products by considering both the quantity and profit factors instead of frequent itemset mining (FIM) of association rules (ARs). In thispaper, an evolutionary algorithm is presented to efficiently mine high-utility itemsets (HUIs) based on the binary particle swarm optimization. A maximal pattern (MP)-tree strcutrue is further designed to solve the combinational problem in the evolutionprocess. Substantial experiments on real-life datasets show that the proposed binary PSO-based algorithm has better results compared to the state-of-the-art GA-based algorithm.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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