4.7 Article

An efficient biobjective evolutionary algorithm for mining frequent and high utility itemsets

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Mining frequent weighted utility itemsets in hierarchical quantitative databases

Ham Nguyen et al.

Summary: This study proposes a new concept of mining frequent weighted utility itemsets in hierarchical quantitative databases and develops two efficient algorithms. The experimental results indicate that FAST_MINE_FWUIS is recommended for mining in this context.

KNOWLEDGE-BASED SYSTEMS (2022)

Article Computer Science, Artificial Intelligence

High-utility itemsets mining based on binary particle swarm optimization with multiple adjustment strategies

Wei Fang et al.

Summary: This study proposes an improved binary particle swarm optimization (HUIM-IBPSO) for high-utility itemset mining (HUIM), addressing the issues of exponential growth search space and time-consuming process in traditional exact algorithms. The proposed approach incorporates multiple adjustment strategies to keep the same HUIs, enhance search ability, avoid premature convergence, and improve efficiency in mining HUIs.

APPLIED SOFT COMPUTING (2022)

Article Computer Science, Information Systems

Efficient mining of cross-level high-utility itemsets in taxonomy quantitative databases

N. T. Tung et al.

Summary: In contrast to frequent itemset mining algorithms, high-utility itemset mining algorithms focus on identifying the most profitable sets of items in transaction databases. However, most existing algorithms overlook item categorizations, which provide useful information in real-world transaction databases. To address this limitation, this study introduces a novel algorithm called FEACP, which efficiently identifies high-utility itemsets of different abstraction levels by incorporating effective pruning strategies. Performance evaluation shows that FEACP is significantly faster and reduces memory usage compared to state-of-the-art algorithms on both sparse and dense databases.

INFORMATION SCIENCES (2022)

Article Computer Science, Artificial Intelligence

Efficient high-utility occupancy itemset mining algorithm on massive data

Jingxuan He et al.

Summary: This paper proposes a novel high utility occupancy itemset mining algorithm SHO, which considers both quantities and profits of itemsets and achieves efficient mining on large-scale databases through techniques such as suffix partitioning, generation pruning, and itemset linking.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

Article Computer Science, Artificial Intelligence

Efficient algorithms for mining closed and maximal high utility itemsets

Hai Duong et al.

Summary: Closed high utility itemsets (CHUIs) and maximal high utility itemsets (MaxHUIs) are important concise representations of HUIs. Mining these representations is crucial for generating meaningful high utility association rules. However, existing algorithms suffer from long runtimes, high memory usage, and scalability issues. To address this, this paper proposes two efficient algorithms that can mine these representations faster.

KNOWLEDGE-BASED SYSTEMS (2022)

Article Automation & Control Systems

Effective algorithms to mine skyline frequent-utility itemsets

Xuan Liu et al.

Summary: This article introduces two new algorithms (EMSFUI-D and EMSFUI-B) for mining skyline frequent-utility itemsets. These algorithms outperform existing algorithms in terms of execution time, memory consumption, and pruning performance.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2022)

Article Computer Science, Artificial Intelligence

High utility itemset mining using binary differential evolution: An application to customer segmentation

Gutha Jaya Krishna et al.

Summary: In this paper, two high utility itemset mining algorithms driven by Binary Differential Evolution (BDE) and Adaptive Binary Differential Evolution (ABDE) were proposed and compared with other existing algorithms on seven datasets. The results showed that the BDE algorithm outperformed other algorithms in terms of mining the maximum number of itemsets.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Article Computer Science, Artificial Intelligence

Explainable Fuzzy Utility Mining on Sequences

Wensheng Gan et al.

Summary: This article investigates explainable fuzzy-theoretic utility mining on multisequences and proposes a novel method termed pattern growth fuzzy utility mining (PGFUM) for mining fuzzy high-utility sequences with linguistic meaning. By utilizing explainable fuzziness in compressed data structures and pruning strategies with upper bounds on explainable fuzzy utility, PGFUM achieves both human-explainable mining results and high efficiency in terms of runtime and memory cost.

IEEE TRANSACTIONS ON FUZZY SYSTEMS (2021)

Article Computer Science, Artificial Intelligence

Efficient closed high-utility pattern fusion model in large-scale databases

Jerry Chun-Wei Lin et al.

Summary: The paper presents a large-scale information fusion architecture to integrate closed high-utility patterns discovered from multiple distributed databases. A generic composite model is used to cluster transactions for correctness and completeness, while the MapReduce framework is deployed to speed up the mining performance of closed high-utility patterns.

INFORMATION FUSION (2021)

Article Computer Science, Artificial Intelligence

A Survey on the Hypervolume Indicator in Evolutionary Multiobjective Optimization

Ke Shang et al.

Summary: This article provides a comprehensive survey on the hypervolume indicator widely used in the field of evolutionary multiobjective optimization. The goal is to help researchers deepen their understanding of the principles and applications of the hypervolume indicator, and to promote further utilization of it.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2021)

Article Computer Science, Information Systems

Discovering high utility-occupancy patterns from uncertain data

Chien-Ming Chen et al.

Summary: This paper introduces a novel algorithm, UHUOPM, for mining high-utility occupancy patterns in uncertain databases, dividing user preferences into three factors: support, probability, and utility occupancy. The algorithm utilizes PUO-list and PFU-table to reduce memory cost and time consumption while also constructing a support count tree (SC-tree) for pruning the search space. Substantial experiments were conducted to evaluate the algorithm's performance on real-life and synthetic datasets, focusing on effectiveness and efficiency.

INFORMATION SCIENCES (2021)

Article Computer Science, Artificial Intelligence

A predictive GA-based model for closed high-utility itemset mining

Jerry Chun-Wei Lin et al.

Summary: This study explores the importance of mining high-utilization patterns in market engineering and proposes a new approach based on clustering models and a compact genetic algorithm to discover high-utility closed patterns more quickly and accurately. Experimental results show that this method outperforms existing methods in terms of runtime performance and mining results.

APPLIED SOFT COMPUTING (2021)

Article Computer Science, Artificial Intelligence

Mining cost-effective patterns in event logs

Philippe Fournier-Viger et al.

KNOWLEDGE-BASED SYSTEMS (2020)

Article Computer Science, Artificial Intelligence

An Evolutionary Algorithm for Large-Scale Sparse Multiobjective Optimization Problems

Ye Tian et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2020)

Proceedings Paper Computer Science, Artificial Intelligence

TKC: Mining Top-K Cross-Level High Utility Itemsets

Mourad Nouioua et al.

20TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2020) (2020)

Article Automation & Control Systems

High average-utility itemset mining with multiple minimum utility threshold: A generalized approach

Krishan Kumar Sethi et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2020)

Article Computer Science, Artificial Intelligence

Metaheuristic research: a comprehensive survey

Kashif Hussain et al.

ARTIFICIAL INTELLIGENCE REVIEW (2019)

Article Computer Science, Artificial Intelligence

Efficient high average-utility itemset mining using novel vertical weak upper-bounds

Tin Truong et al.

KNOWLEDGE-BASED SYSTEMS (2019)

Article Computer Science, Interdisciplinary Applications

A survey on new generation metaheuristic algorithms

Tansel Dokeroglu et al.

COMPUTERS & INDUSTRIAL ENGINEERING (2019)

Article Automation & Control Systems

Mining of skyline patterns by considering both frequent and utility constraints

Jerry Chun-Wei Lin et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2019)

Article Computer Science, Information Systems

Improved Genetic Algorithm for High-Utility Itemset Mining

Qiang Zhang et al.

IEEE ACCESS (2019)

Proceedings Paper Engineering, Electrical & Electronic

A Closed Itemset Property based Multi-objective Evolutionary Approach for Mining Frequent and High Utility Itemsets

Heng Cao et al.

2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) (2019)

Article Computer Science, Artificial Intelligence

A Surrogate-Assisted Multiobjective Evolutionary Algorithm for Large-Scale Task-Oriented Pattern Mining

Ye Tian et al.

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE (2019)

Article Computer Science, Artificial Intelligence

A multi-objective evolutionary approach for mining frequent and high utility itemsets

Lei Zhang et al.

APPLIED SOFT COMPUTING (2018)

Article Computer Science, Artificial Intelligence

A Framework for Large-Scale Multiobjective Optimization Based on Problem Transformation

Heiner Zille et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2018)

Article Computer Science, Artificial Intelligence

A Decision Variable Clustering-Based Evolutionary Algorithm for Large-Scale Many-Objective Optimization

Xingyi Zhang et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2018)

Article Computer Science, Artificial Intelligence

A binary PSO approach to mine high-utility itemsets

Jerry Chun-Wei Lin et al.

SOFT COMPUTING (2017)

Article Computer Science, Artificial Intelligence

Pattern Recommendation in Task-Oriented Applications: A Multi-Objective Perspective

Xingyi Zhang et al.

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE (2017)

Article Computer Science, Artificial Intelligence

Efficiently mining of skyline frequent-utility patterns

Jeng-Shyang Pan et al.

INTELLIGENT DATA ANALYSIS (2017)

Article Automation & Control Systems

A general Evolutionary Framework for different classes of Critical Node Problems

Roberto Aringhieri et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2016)

Article Automation & Control Systems

Mining high-utility itemsets based on particle swarm optimization

Jerry Chun-Wei Lin et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2016)

Article Computer Science, Artificial Intelligence

A Multiobjective Evolutionary Algorithm Based on Decision Variable Analyses for Multiobjective Optimization Problems With Large-Scale Variables

Xiaoliang Ma et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2016)

Article Computer Science, Artificial Intelligence

Efficient Algorithms for Mining Top-K High Utility Itemsets

Vincent S. Tseng et al.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2016)

Article Computer Science, Information Systems

Revisiting bound estimation of pattern measures: A generic framework

Lei Zhang et al.

INFORMATION SCIENCES (2016)

Article Computer Science, Information Systems

Approximate non-dominated sorting for evolutionary many-objective optimization

Xingyi Zhang et al.

INFORMATION SCIENCES (2016)

Article Computer Science, Artificial Intelligence

A Knee Point-Driven Evolutionary Algorithm for Many-Objective Optimization

Xingyi Zhang et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2015)

Article Computer Science, Artificial Intelligence

A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling

Ran Cheng et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2015)

Article Computer Science, Artificial Intelligence

Top-k high utility pattern mining with effective threshold raising strategies

Heungmo Ryang et al.

KNOWLEDGE-BASED SYSTEMS (2015)

Article Computer Science, Artificial Intelligence

Discovery of High Utility Itemsets Using Genetic Algorithm with Ranked Mutation

S. Kannimuthu et al.

APPLIED ARTIFICIAL INTELLIGENCE (2014)

Article Computer Science, Artificial Intelligence

Fast mining frequent itemsets using Nodesets

Zhi-Hong Deng et al.

EXPERT SYSTEMS WITH APPLICATIONS (2014)

Article Computer Science, Information Systems

A survey on optimization metaheuristics

Ilhern Boussaid et al.

INFORMATION SCIENCES (2013)

Article Computer Science, Information Systems

Mining numerical association rules via multi-objective genetic algorithms

B. Minaei-Bidgoli et al.

INFORMATION SCIENCES (2013)

Article Automation & Control Systems

Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach

Bing Xue et al.

IEEE TRANSACTIONS ON CYBERNETICS (2013)

Article Computer Science, Artificial Intelligence

Multi-objective feature selection by using NSGA-II for customer churn prediction in telecommunications

Bingquan Huang et al.

EXPERT SYSTEMS WITH APPLICATIONS (2010)

Article Computer Science, Artificial Intelligence

Isolated items discarding strategy for discovering high utility itemsets

Yu-Chiang Li et al.

DATA & KNOWLEDGE ENGINEERING (2008)

Article Computer Science, Artificial Intelligence

A faster algorithm for calculating hypervolume

L While et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2006)

Article Computer Science, Artificial Intelligence

A fast and elitist multiobjective genetic algorithm: NSGA-II

K Deb et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2002)

Article Computer Science, Artificial Intelligence

Scalable algorithms for association mining

MJ Zaki

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2000)