Results 41 to 50 of about 530 (210)

TargetUM: Targeted High-Utility Itemset Querying

CoRR, 2021
Preprint.
Jinbao Miao, Shicheng Wan, Wensheng Gan, Jiayi Sun 0002, Jiahui Chen 0002   +4 more
openaire   +2 more sources

A survey of itemset mining

, 2017
Itemset mining is an important subfield of data mining, which consists of discovering interesting and useful patterns in transaction databases. The traditional task of frequent itemset mining is to discover groups of items (itemsets) that appear ...
Jerry Chun‐Wei Lin, Vo, Bay, Bay Vo, Tin Truong Chi, Zhang, Ji, Philippe Fournier‐Viger, Hoai Bac Le, Chi, Tin Truong, Le, Hoai Bac, Lin, Jerry Chun-Wei, Ji Zhang, Fournier-Viger, Philippe   +11 more
core   +1 more source

Improved Genetic Algorithm for High-Utility Itemset Mining

IEEE Access, 2019
High-utility itemset mining (HUIM) is an important research topic in the data mining field. Typically, traditional HUIM algorithms must handle the exponential problem of huge search space when the database size or number of distinct items is very large ...
Qiang Zhang, Wei Fang, Jun Sun, Quan Wang   +3 more
doaj   +1 more source

Pruning Strategy on Adaptive Rule Model by Sorting Utility Items

IEEE Access, 2022
The adaptive Rule Model is an association rule development that formulates a minimum threshold value according to the data characteristics. The formulation process is based on item frequency and utility for other considerations, which requires high ...
Erna Hikmawati, Nur Ulfa Maulidevi, Kridanto Surendro   +2 more
doaj   +1 more source

Parallel Mining Algorithm for the Enumeration Space of Closed High Utility Itemsets

Journal of Harbin University of Science and Technology
To address the issues of result redundancy and time overhead in high-dimensional data environments, a closed high utility itemset mining algorithm, SpCHUIM (Closed High Utility Itemsets Mining on Spark), is proposed.
LI Chengyan, SUN Anqi, LIU Songlin
doaj   +1 more source

An Evolutionary Algorithm to Mine High-Utility Itemsets

Advances in Electrical and Electronic Engineering, 2015
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) of association rules (ARs). In this
Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Jaroslav Frnda, Lukas Sevcik, Miroslav Voznak   +5 more
doaj   +1 more source

Closed High Utility Pattern Mining over Data Stream Based on Projection in the Window

Taiyuan Ligong Daxue xuebao, 2022
A fast and effective algorithm EFIM_Closed_DS was proposed to mine closed and high utility itemsets in the data stream environment. The algorithm is based on the projection technology in the window, and the database projection technology and transaction ...
Muhang LI, Meng HAN, Zhiqiang CHEN, Hongxin WU, Xilong ZHANG   +4 more
doaj   +1 more source

Double‐Edged Sword of Social Media Algorithms: Assessing the Risks to University Cybersecurity and Student Data Privacy

Engineering Reports, Volume 8, Issue 5, May 2026.
Social media algorithms drive a hidden risk chain: over‐disclosure → behavioral fusion → targeted attacks. We propose a 128‐dim, law‐aware risk scoring model with Drools‐based dynamic alerts for universities. ABSTRACT As universities undergo accelerated digital transformation, social media algorithms—while streamlining campus services—have emerged as a
Weishu Ye, Zhi Li
wiley   +1 more source

Developing and Validating an Instrument for Assessing Secondary Students' Self‐Efficacy for Online Reading

Reading Research Quarterly, Volume 61, Issue 2, April/May/June 2026.
This study introduces and validates the Self‐Efficacy for Online Reading Questionnaire (SEORQ), a process‐grounded instrument designed to measure secondary students' efficacy in executing the core demands of online reading. The model conceptualizes online reading self‐efficacy as a multidimensional construct encompassing five interrelated processes ...
SeongYeup Kim, Yongjun Lee, Elena Forzani   +2 more
wiley   +1 more source

Personalized and Explainable Aspect‐Based Recommendation Using Latent Opinion Groups

Computational Intelligence, Volume 42, Issue 2, April 2026.
ABSTRACT The problem of explainable recommendation—supporting the recommendation of a product or service with an explanation of why the item is a good choice for the user—is attracting substantial research attention recently. Recommendations associated with an explanation of how the aspects of the chosen item may meet the needs and preferences of the ...
Maryam Mirzaei, Jörg Sander, Eleni Stroulia   +2 more
wiley   +1 more source