Results 41 to 50 of about 905 (211)
Improved Genetic Algorithm for High-Utility Itemset Mining
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 +3 more
doaj +1 more source
Pruning Strategy on Adaptive Rule Model by Sorting Utility Items
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 +2 more
doaj +1 more source
Parallel Mining Algorithm for the Enumeration Space of Closed High Utility Itemsets
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
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 +5 more
doaj +1 more source
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
Closed High Utility Pattern Mining over Data Stream Based on Projection in the Window
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 +4 more
doaj +1 more source
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 +2 more
wiley +1 more source
Personalized and Explainable Aspect‐Based Recommendation Using Latent Opinion Groups
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 +2 more
wiley +1 more source
Mining of high average-utility patterns with item-level thresholds
In this paper, we introduce a level-wise algorithm named High Average-Utility Itemset Mining with Multiple Minimum Average-Utility threshold (HAUIM-MMAU), which relies on a novel transaction-maximum utility downward closure (TMUDC) property and a concept
Zhang, Ji +4 more
core +1 more source
Critical Review for One‐Class Classification: Recent Advances and Reality Behind Them
This review presents a new taxonomy to summarize one‐class classification (OCC) algorithms and their applications. The main argument is that OCC should not learn multiple classes. The paper highlights common violations of OCC involving multiple classes.
Toshitaka Hayashi +3 more
wiley +1 more source

