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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10200 - Computer and information sciences

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

IEEE Access

ISSN

2169-3536

e-ISSN

2169-3536

Svazek periodika

11

Číslo periodika v rámci svazku

září 2023

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

17

Strana od-do

104789-104805

Kód UT WoS článku

001081582600001

EID výsledku v databázi Scopus

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