A binary PSO approach to mine high-utility itemsets

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A86098028" target="_blank" >RIV/61989100:27240/17:86098028 - isvavai.cz</a>

Alternative codes found

RIV/61989100:27740/17:86098028

Result on the web

<a href="https://link.springer.com/article/10.1007%2Fs00500-016-2106-1" target="_blank" >https://link.springer.com/article/10.1007%2Fs00500-016-2106-1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00500-016-2106-1" target="_blank" >10.1007/s00500-016-2106-1</a>

Result language

angličtina

Original language name

A binary PSO approach to mine high-utility itemsets

Original language description

High-utility itemset mining (HUIM) is a critical issue in recent years since it can be used to reveal the profitable products by considering both the quantity and profit factors instead of frequent itemset mining (FIM) or association-rule mining (ARM). Several algorithms have been presented to mine high-utility itemsets (HUIs) and most of them have to handle the exponential search space for discovering HUIs when the number of distinct items and the size of database are very large. In the past, a heuristic HUPE(Formula presented.)-GRAM algorithm was proposed to mine HUIs based on genetic algorithm (GA). For the evolutionary computation (EC) techniques of particle swarm optimization (PSO), it only requires fewer parameters compared to the GA-based approaches. Since the traditional PSO mechanism is used to handle the continuous problem, in this paper, the discrete PSO is adopted to encode the particles as the binary variables. An efficient PSO-based algorithm, namely HUIM-BPSO, is proposed to efficiently find HUIs. The designed HUIM-BPSO algorithm finds the high-transaction-weighted utilization 1-itemsets (1-HTWUIs) as the size of the particles based on transaction-weighted utility (TWU) model, which can greatly reduce the combinational problem in evolution process. The sigmoid function is adopted in the updating process of the particles for the designed HUIM-BPSO algorithm. An OR/NOR-tree structure is further developed to reduce the invalid combinations for discovering HUIs. Substantial experiments on real-life datasets show that the proposed algorithm outperforms the other heuristic algorithms for mining HUIs in terms of execution time, number of discovered HUIs, and convergence. © 2016 Springer-Verlag Berlin Heidelberg

Czech name

—

Czech description

—

Type

J_imp - 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)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2017

Confidentiality

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

Name of the periodical

Soft computing

ISSN

1432-7643

e-ISSN

—

Volume of the periodical

21

Issue of the periodical within the volume

17

Country of publishing house

US - UNITED STATES

Number of pages

19

Pages from-to

5103-5121

UT code for WoS article

000408231900020

EID of the result in the Scopus database

2-s2.0-84960115620