Results 31 to 40 of about 2,974 (185)
Effective pattern discovery for text mining [PDF]
, 2012 Many data mining techniques have been proposed for mining useful patterns in text documents. However, how to effectively use and update discovered patterns is still an open research issue, especially in the domain of text mining. Since most existing text
Li, Yuefeng, Wu, Sheng-Tang, Zhong, Ning
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Efficient Analysis of Pattern and Association Rule Mining Approaches
, 2014 The process of data mining produces various patterns from a given data source. The most recognized data mining tasks are the process of discovering frequent itemsets, frequent sequential patterns, frequent sequential rules and frequent association rules.
Lazzez, Amor, Slimani, Thabet
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Parallel Mining Algorithm for the Enumeration Space of Closed High Utility Itemsets
Journal of Harbin University of Science and TechnologyTo 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
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Mining for Useful Association Rules Using the ATMS [PDF]
, 2006 Association rule mining has made many achievements in the area of knowledge discovery in databases. Recent years, the quality of the extracted association rules has drawn more and more attention from researchers in data mining community.
Li, Yuefeng, Xu, Yue
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PARALLEL MINING OF FREQUENT MAXIMAL ITEMSETS USING ORDER PRESERVING GENERATORS [PDF]
ICTACT Journal on Soft Computing, 2010 In this paper, we propose a parallel algorithm for mining maximal itemsets. We propose POP-MAX (Parallel Order Preserving MAXimal itemset algorithm), a fast and memory efficient parallel algorithm which enumerates all the maximal patterns concurrently ...
R.V. Nataraj, S. Selvan
doaj
Class Association Rule Pada Metode Associative Classification
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2011 Frequent patterns (itemsets) discovery is an important problem in associative classification rule mining. Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP)-growth, and Transaction Data Location (Tid)-list ...
Eka Karyawati, Edi Winarko
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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 +2 more
wiley +1 more source
IEEE AccessTraditional pattern mining algorithms are based on tree and linked list structures. However, they often only consider a single factor of frequency or utility and have to deal with exponential search spaces as well as generate numerous candidates.
Xiumei Zhao, Xincheng Zhong, Bing Han
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Critical Review for One‐Class Classification: Recent Advances and Reality Behind Them
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 1, March 2026.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
A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM
IEEE AccessFrequent 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
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