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Memory issues in frequent itemset mining
Proceedings of the 2004 ACM symposium on Applied computing, 2004During the past decade, many algorithms have been proposed to solve the frequent itemset mining problem, i.e. find all sets of items that frequently occur together in a given database of transactions. Although very efficient techniques have been presented, they still suffer from the same problem. That is, they are all inherently dependent on the amount
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Frequent Itemset Mining with Parallel RDBMS
2005Data mining on large relational databases has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind specialized implementation. We investigate approaches based on SQL for the problem of finding frequent patterns from a transaction table, including an algorithm that we ...
Xuequn Shang 0001, Kai-Uwe Sattler
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Frequent itemset mining on graphics processors
Proceedings of the Fifth International Workshop on Data Management on New Hardware, 2009We present two efficient Apriori implementations of Frequent Itemset Mining (FIM) that utilize new-generation graphics processing units (GPUs). Our implementations take advantage of the GPU's massively multi-threaded SIMD (Single Instruction, Multiple Data) architecture.
Wenbin Fang +4 more
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An Approximate Approach to Frequent Itemset Mining
2017 IEEE Second International Conference on Data Science in Cyberspace (DSC), 2017Eclat algorithm is one of the most widely used frequent itemset mining methods. One significant bottleneck of the Eclat algorithm is that the efficiency for calculating the intersection of itemsets is low especially when the itemsets have a large number of transactions.
Chunkai Zhang, Xudong Zhang, Panbo Tian
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Mining Frequent Itemsets in Evidential Database
2014Mining frequent patterns is widely used to discover knowledge from a database. It was originally applied on Market Basket Analysis (MBA) problem which represents the Boolean databases. In those databases, only the existence of an article (item) in a transaction is defined.
Ahmed Samet +2 more
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Parametric Algorithms for Mining Share Frequent Itemsets
Journal of Intelligent Information Systems, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Brock Barber, Howard J. Hamilton
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Mining Maximal Frequent Itemsets with Frequent Pattern List
Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007), 2007Mining frequent itemsets is a major aspect of association rule research. However, the mining of the complete of frequent itemsets will lead to a huge number of itemsets. Fortunately, this problem can be reduced to the mining of maximal frequent itemsets.
Jin Qian, Feiyue Ye
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Frequent Itemset Mining in Multirelational Databases
2009This paper proposes a new approach to mine multirelational databases. Our approach is based on the representation of a multirelational database as a set of trees. Tree mining techniques can then be applied to identify frequent patterns in this kind of databases.
Aída Jiménez +2 more
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The Research of Sampling for Mining Frequent Itemsets
2006Efficiently mining frequent itemsets is the key step in extracting association rules from large scale databases. Considering the restriction of min_support in mining association rules, a weighted sampling algorithm for mining frequent itemsets is proposed in the paper. First of all, a weight is given to each transaction data.
Xuegang Hu, Haitao Yu
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FPGA/GPU-based Acceleration for Frequent Itemsets Mining: A Comprehensive Review
ACM Computing Surveys, 2022Martin Letras-Luna +2 more
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