Mining Top-K High Utility Itemsets Using Bio-Inspired Algorithms with a Diversity within Population Framework

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F22%3A63559518" target="_blank" >RIV/70883521:28140/22:63559518 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/RIVF55975.2022.10013891" target="_blank" >http://dx.doi.org/10.1109/RIVF55975.2022.10013891</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/RIVF55975.2022.10013891" target="_blank" >10.1109/RIVF55975.2022.10013891</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Mining Top-K High Utility Itemsets Using Bio-Inspired Algorithms with a Diversity within Population Framework

Popis výsledku v původním jazyce

High-utility itemset mining (HUIM), as a necessary data mining task, has paid the attention of many researchers. It includes numerous applications in various arears. Recently, a method, which improved the memory usage and runtime for HUIs mining, was proposed, is called TKO-BPSO. It helps to automatically increase the border thresholds and might considerably reduce the combinational problem for pruning the search space effectively. However, the idea only works to maintain the current optimal values in the next populations, leading to the variety within populations is limited. To handle this problem, we propose a new bio-inspired algorithm-based HUIM framework to explore HUIs, namely TKO-HUIMF-PSO (Top-K high utility itemset mining in One phase based on a HUIM Framework of Particle Swarm Optimization). The main idea of TKO-HUIMF-PSO adapts the standard roadmap of bio-inspired algorithms by applying roulette wheel selection to all the discovered HUIs to determine the target values of the next population. Consequently, it improves the diversity within populations. Significant experiments conducted on publicly available several real and synthetic datasets delineate that the proposed algorithm is efficient and effective in terms of runtime and memory usage.

Název v anglickém jazyce

Mining Top-K High Utility Itemsets Using Bio-Inspired Algorithms with a Diversity within Population Framework

Popis výsledku anglicky

High-utility itemset mining (HUIM), as a necessary data mining task, has paid the attention of many researchers. It includes numerous applications in various arears. Recently, a method, which improved the memory usage and runtime for HUIs mining, was proposed, is called TKO-BPSO. It helps to automatically increase the border thresholds and might considerably reduce the combinational problem for pruning the search space effectively. However, the idea only works to maintain the current optimal values in the next populations, leading to the variety within populations is limited. To handle this problem, we propose a new bio-inspired algorithm-based HUIM framework to explore HUIs, namely TKO-HUIMF-PSO (Top-K high utility itemset mining in One phase based on a HUIM Framework of Particle Swarm Optimization). The main idea of TKO-HUIMF-PSO adapts the standard roadmap of bio-inspired algorithms by applying roulette wheel selection to all the discovered HUIs to determine the target values of the next population. Consequently, it improves the diversity within populations. Significant experiments conducted on publicly available several real and synthetic datasets delineate that the proposed algorithm is efficient and effective in terms of runtime and memory usage.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings - 2022 RIVF International Conference on Computing and Communication Technologies, RIVF 2022

ISBN

978-1-66546-166-5

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

—

Název nakladatele

Institute of Electrical and Electronics Engineers Inc.

Místo vydání

Piscataway, New Jersey

Místo konání akce

Ho Chi Minh City

Datum konání akce

20. 12. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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