Results 51 to 60 of about 45,837 (241)
A novel pruning algorithm for mining long and maximum length frequent itemsets
Expert systems with applications, 2020 Frequent itemset mining is today one of the most popular data mining techniques. Its application is, however, hindered by the high computational cost in many real-world datasets, especially for smaller values of support thresholds.
Sina Lessanibahri +2 more
semanticscholar +1 more source
Incremental Updating Algorithm of Parallel Association Rule Based on MapReduce [PDF]
Jisuanji gongcheng, 2016 Under the environment of big data,the traditional association rule mining algorithms have lower efficiency caused by the rapidly increasing data.Aiming at the problem,this paper proposes a parallel incremental updating algorithm of association rules ...
CHENG Guang,WANG Xiaofeng
doaj +1 more source
Knowledge, false beliefs and fact-driven perceptions of Muslims in Australia: a national survey
, 2005 Mining frequent itemsets is one of the main problems in data mining. Much effort went into developing efficient and scalable algorithms for this problem.
Bart Goethals, Toon Calders
core +2 more sources
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 +2 more
wiley +1 more source
A Model-Based Frequency Constraint for Mining Associations from Transaction Data
, 2006 Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an association, is used as the primary indicator of the associations's significance.
Hahsler, Michael
core +3 more sources
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
Generic Itemset Mining Based on Reinforcement Learning
IEEE Access, 2022 One of the biggest problems in itemset mining is the requirement of developing a data structure or algorithm, every time a user wants to extract a different type of itemsets.
Kazuma Fujioka, Kimiaki Shirahama
doaj +1 more source
FP-tree and COFI Based Approach for Mining of Multiple Level Association Rules in Large Databases
, 2010 In recent years, discovery of association rules among itemsets in a large database has been described as an important database-mining problem. The problem of discovering association rules has received considerable research attention and several ...
Kumar, Parveen +2 more
core +1 more source
Geoscience Data Journal, Volume 13, Issue 1, January 2026.We build a new, open‐source global copper deposit dataset (GCDD), facilitating AI‐driven data analysis for exploration targeting and improving our understanding of copper mineralizing systems and their mappable expressions. The GCDD hosts information about 1483 copper deposits worldwide, capturing key deposit attributes such as location, genetic type ...
Bin Wang +2 more
wiley +1 more source
Mining frequent closed itemsets out of core [PDF]
Proceedings of the 2006 SIAM International Conference on Data Mining, 2006 Extracting frequent itemsets is an important task in many data mining applications. When data are very large, it becomes mandatory to perform the mining task by using an external memory algorithm, but only a few of these algorithms have been proposed so far.
LUCCHESE, Claudio +2 more
openaire +3 more sources