A hierarchical set-enumeration tree enabling high occupancy item set mining and the use of an adaptive occupancy threshold
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10256169" target="_blank" >RIV/61989100:27240/25:10256169 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/25:10256169
Result on the web
<a href="https://link.springer.com/article/10.1007/s10489-024-06166-7" target="_blank" >https://link.springer.com/article/10.1007/s10489-024-06166-7</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10489-024-06166-7" target="_blank" >10.1007/s10489-024-06166-7</a>
Alternative languages
Result language
angličtina
Original language name
A hierarchical set-enumeration tree enabling high occupancy item set mining and the use of an adaptive occupancy threshold
Original language description
The highly efficient HEP algorithm is a useful tool for mining High Occupancy (HO) item sets. Occupancy is an important measure that describes the interestingness of frequent item sets. The current study examines the efficiency problems in mining HO item sets and proposes an improved HEP algorithm, named advanced HEP (A-HEP), based on set theory rules which eliminate a large number of redundant iterations. The study also proposes a novel adaptive-and-modified HEP (NAM-HEP) algorithm that uses HO Set-Enumeration (SE) trees to store HO item sets. The study proposes definitions for adaptive thresholds such as support threshold and occupancy threshold based on the attributes of the transaction database for efficient pruning of the HO-SE tree. Two pseudo-code blocks are presented in addition to a detailed description of the A-HEP and NAM-HEP algorithms and their advantages. Using the A-HEP and NAM-HEP algorithms, HO item sets are investigated from the practical transaction databases named mushroom and retail. The results indicate that the proposed A-HEP and NAM-HEP algorithms enhance mining performance and runtime benchmarks.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Applied Intelligence
ISSN
0924-669X
e-ISSN
1573-7497
Volume of the periodical
55
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
21
Pages from-to
"55:205"
UT code for WoS article
001383333200008
EID of the result in the Scopus database
—