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

Result code in 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>
Result on the web
<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>

Result language
angličtina
Original language name
Mining Top-K High Utility Itemsets Using Bio-Inspired Algorithms with a Diversity within Population Framework
Original language description
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.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings - 2022 RIVF International Conference on Computing and Communication Technologies, RIVF 2022
ISBN
978-1-66546-166-5
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
Piscataway, New Jersey
Event location
Ho Chi Minh City
Event date
Dec 20, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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