FTKHUIM: A Fast and Efficient Method for Mining Top-K High-Utility Itemsets

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10253796" target="_blank" >RIV/61989100:27240/23:10253796 - isvavai.cz</a>

Result on the web

<a href="https://ieeexplore.ieee.org/document/10250768" target="_blank" >https://ieeexplore.ieee.org/document/10250768</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2023.3314984" target="_blank" >10.1109/ACCESS.2023.3314984</a>

Result language

angličtina

Original language name

FTKHUIM: A Fast and Efficient Method for Mining Top-K High-Utility Itemsets

Original language description

High-utility itemset mining (HUIM) is an important task in the field of knowledge data discovery. The large search space and huge number of HUIs are the consequences of applying HUIM algorithms with an inappropriate user-defined minimum utility threshold value. Determining a suitable threshold value to obtain the expected results is not a simple task and requires spending a lot of time. For common users, it is difficult to define a minimum threshold utility for exploring the right number of HUIs. On the one hand, if the threshold is set too high then the number of HUIs would not be enough. On the other hand, if the threshold is set too low, too many HUIs will be mined, thus wasting both time and memory. The top-k HUIs mining problem was proposed to solve this issue, and many effective algorithms have since been introduced by researchers. In this research, a novel approach, namely FTKHUIM (Fast top-k HUI Mining), is introduced to explore the top-k HUIs. One new threshold-raising strategy called RTU, a transaction utility (TU)-based threshold-raising strategy, has also been shown to rapidly increase the speed of top-k HUIM. The study also proposes a global structure to store utility values in the process of applying raising-threshold strategies to optimize these strategies. The results of experiments on various datasets prove that the FTKHUIM algorithm achieves better results with regard to both the time and search space needed.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

10200 - Computer and information sciences

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Access

ISSN

2169-3536

e-ISSN

2169-3536

Volume of the periodical

11

Issue of the periodical within the volume

září 2023

Country of publishing house

US - UNITED STATES

Number of pages

17

Pages from-to

104789-104805

UT code for WoS article

001081582600001

EID of the result in the Scopus database

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