Results 41 to 50 of about 719,228 (260)
SWEclat: a frequent itemset mining algorithm over streaming data using Spark Streaming
Finding frequent itemsets in a continuous streaming data is an important data mining task which is widely used in network monitoring, Internet of Things data analysis and so on.
Wen Xiao, Juan Hu
semanticscholar +1 more source
High-utility Itemsets Mining Algorithm Based on Double Binary Particle Swarm Optimization [PDF]
High-utility itemset mining algorithm is an important part of association analysis.By improving the basic binary particle swarm optimization algorithm,a Double Binary Particle Swarm Optimization(DBPSO) algorithm is proposed.The minimum utility threshold ...
JIN Xiaole,LIU Xiabi,MA Xiao
doaj +1 more source
Users Constraints in Itemset Mining
Discovering significant itemsets is one of the fundamental problems in data mining. It has recently been shown that constraint programming is a flexible way to tackle data mining tasks. With a constraint programming approach, we can easily express and efficiently answer queries with users constraints on items.
Christian Bessiere +3 more
openaire +2 more sources
DISCOVERING CONFUSING FREQUENT ITEMSETS
Frequent itemset mining is one of the most important research areas in the field of association rule mining. Exploiting frequent itemsets at different abstraction levels of data will yield valuable knowledge.
Huỳnh Thành Lộc
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Apriori algorithm is one of the methods with regard to association rules in data mining. This algorithm uses knowledge from an itemset previously formed with frequent occurrence frequencies to form the next itemset.
Adie Wahyudi Oktavia Gama +1 more
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A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM
Frequent itemset mining (FIM) and high utility itemset mining (HUIM) are popular data mining techniques used in various real-world applications such as retail-market, bio-medicine, and click-stream analysis.
Muhammad Waheed Ashraf +2 more
doaj +1 more source
Actionable high-coherent-utility fuzzy itemset mining
Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from quantitative transaction databases.
Chen, C. H.;Li, A. F.;Lee, Y. C. +1 more
core +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
AbstrakAlgoritma yang umum digunakan dalam proses pencarian frequent itemset (data yang paling sering muncul) adalah Apriori. Tetapi Algoritma Apriori mempunyai memiliki kekurangan yaitu membutuhkan waktu yang lama dalam proses pencarian frequent itemset.
Wirdah Choiriah
doaj +3 more sources
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

