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An Efficient Frequent Pattern Mining Algorithm
2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009Efficient algorithms for mining frequent itemsets are crucial for mining association rules and for other data mining tasks. FP-growth algorithm has been implemented using a prefix-tree structure, known as a FP-tree, for storing compressed frequency information.
Jun Tan, Yingyong Bu, Bo Yang
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Multi-level Frequent Pattern Mining
2009Frequent pattern mining (FPM) has become one of the most popular data mining approaches for the analysis of purchasing patterns. Methods such as Apriori and FP-growth have been shown to work efficiently in this setting. However, these techniques are typically restricted to a single concept level.
Todd Eavis, Xi Zheng
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Parallel Mining of Frequent Subtree Patterns
2020Mining frequent subtree patterns in a tree database (or, forest) is useful in domains such as bioinformatics and mining semi-structured data. We consider the problem of mining embedded subtrees in a database of rooted, labeled, and ordered trees. We compare two existing serial mining algorithms, PrefixTreeSpan and TreeMiner, and adapt them for parallel
Wenwen Qu +5 more
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Distributed approximate mining of frequent patterns
Proceedings of the 2005 ACM symposium on Applied computing, 2005This paper discusses a novel communication effcient distributed algorithm for approximate mining of frequent patterns from transactional databases. The proposed algorithm consists in the distributed exact computation of locally frequent itemsets and an effective method for inferring the local support of locally unfrequent itemsets.
SILVESTRI, Claudio, ORLANDO, Salvatore
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Mining Frequent Composite Service Patterns
2008 Seventh International Conference on Grid and Cooperative Computing, 2008Service mining is an important technology which could help service composition. This paper mainly studied the problem of mining frequent composite services from the log of the composition-oriented service discovery system. First, a composite service representation method based on n-tuple was proposed.
Hui Meng +4 more
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Mining Frequent 3D Sequential Patterns
18th International Conference on Scientific and Statistical Database Management (SSDBM'06), 2006We propose a mining approach, MSP, to find the Maximal Sequential 3D Patterns with the constraints of minimum support and minimum confidence. Each pattern is a group of similar sequential 3D objects appearing in a given dataset. Mining sequential patterns in terms of 3D coordinates is important and meaningful in many real-life applications.
Zhenqiang Tan, Anthony K. H. Tung
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Frequent Pattern Mining in Attributed Trees
2013Frequent pattern mining is an important data mining task with a broad range of applications. Initially focused on the discovery of frequent itemsets, studies were extended to mine structural forms like sequences, trees or graphs. In this paper, we introduce a new data mining method that consists in mining new kind of patterns in a collection of ...
Claude Pasquier +3 more
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Methods for Mining Frequent Sequential Patterns
2003We consider the problem of finding frequent subsequences in sequential data. We examine three algorithms using a trie with K levels. The O(K2n) breadth-first (BF) algorithm inserts a pattern into the trie at level k only if level k-1 has been completed.
Linhui Jiang, Howard J. Hamilton
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