Frequent itemset mining: A 25 years review

JM Luna, P Fournier‐Viger… - … Reviews: Data Mining …, 2019 - Wiley Online Library
Frequent itemset mining (FIM) is an essential task within data analysis since it is responsible
for extracting frequently occurring events, patterns, or items in data. Insights from such …

A survey on association rules mining using heuristics

SM Ghafari, C Tjortjis - Wiley Interdisciplinary Reviews: Data …, 2019 - Wiley Online Library
Association rule mining (ARM) is a commonly encountred data mining method. There are
many approaches to mining frequent rules and patterns from a database and one among …

A survey of evolutionary computation for association rule mining

A Telikani, AH Gandomi, A Shahbahrami - Information Sciences, 2020 - Elsevier
Abstract Association Rule Mining (ARM) is a significant task for discovering frequent patterns
in data mining. It has achieved great success in a plethora of applications such as market …

ACROA: artificial chemical reaction optimization algorithm for global optimization

B Alatas - Expert Systems with Applications, 2011 - Elsevier
Heuristic based computational algorithms are densely being used in many different fields
due to their advantages. When investigated carefully, chemical reactions possess efficient …

Combining Apriori heuristic and bio-inspired algorithms for solving the frequent itemsets mining problem

Y Djenouri, M Comuzzi - Information Sciences, 2017 - Elsevier
Abstract Exact approaches to Frequent Itemsets Mining (FIM) are characterised by poor
runtime performance when dealing with large database instances. Several FIM bio-inspired …

Mining high utility itemsets with hill climbing and simulated annealing

MS Nawaz, P Fournier-Viger, U Yun, Y Wu… - ACM Transactions on …, 2021 - dl.acm.org
High utility itemset mining (HUIM) is the task of finding all items set, purchased together, that
generate a high profit in a transaction database. In the past, several algorithms have been …

MODENAR: Multi-objective differential evolution algorithm for mining numeric association rules

B Alatas, E Akin, A Karci - Applied Soft Computing, 2008 - Elsevier
In this paper, a Pareto-based multi-objective differential evolution (DE) algorithm is
proposed as a search strategy for mining accurate and comprehensible numeric association …

Performance analysis of multi-objective artificial intelligence optimization algorithms in numerical association rule mining

E Varol Altay, B Alatas - Journal of Ambient Intelligence and Humanized …, 2020 - Springer
Association rules mining (ARM) is one of the most popular tasks of data mining. Although
there are many effective algorithms run on binary or discrete-valued data for the problem of …

A novel hybrid GA–PSO framework for mining quantitative association rules

F Moslehi, A Haeri, F Martínez-Álvarez - soft computing, 2020 - Springer
Discovering association rules is a useful and common technique for data mining in which
dependencies among datasets are shown. Discovering the rules from continuous numeric …

A modified multi-objective slime mould algorithm with orthogonal learning for numerical association rules mining

S Yacoubi, G Manita, H Amdouni, S Mirjalili… - Neural Computing and …, 2023 - Springer
Association rule mining (ARM) is defined by its crucial role in finding common pattern in data
mining. It has different types such as fuzzy, binary, numerical. In this paper, we introduce a …