Results 11 to 20 of about 8,898 (200)
Personalized Privacy-Preserving Frequent Itemset Mining Using Randomized Response [PDF]
The Scientific World Journal, 2014 Frequent itemset mining is the important first step of association rule mining, which discovers interesting patterns from the massive data. There are increasing concerns about the privacy problem in the frequent itemset mining.
Chongjing Sun +3 more
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Quick mining in dense data: applying probabilistic support prediction in depth-first order [PDF]
PeerJ Computer ScienceFrequent itemset mining (FIM) is a major component in association rule mining, significantly influencing its performance. FIM is a computationally intensive nondeterministic polynomial time (NP)-hard problem.
Muhammad Sadeequllah +3 more
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Research on association analysis between electricity consumption behaviors and weather factors based on mapreduce [PDF]
Scientific ReportsThe change of weather factors will lead to great changes in users’ electricity consumption behaviors. In order to discover the associations between users’ electricity consumption behavior and weather factors, and meet the needs of efficient mining of ...
Yuehua Yang, Yun Wu
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Memory-efficient frequent-itemset mining
Proceedings of the 14th International Conference on Extending Database Technology, 2011 Efficient discovery of frequent itemsets in large datasets is a key component of many data mining tasks. In-core algorithms---which operate entirely in main memory and avoid expensive disk accesses---and in particular the prefix tree-based algorithm FP-growth are generally among the most efficient of the available algorithms.
Schlegel, Benjamin +2 more
openaire +3 more sources
Mining All Non-derivable Frequent Itemsets [PDF]
, 2002 3 ...
Calders, T., GOETHALS, Bart
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Mining Frequent Itemsets in a Stream [PDF]
Seventh IEEE International Conference on Data Mining (ICDM 2007), 2007 We study the problem of finding frequent itemsets in a continuous stream of transactions. The current frequency of an itemset in a stream is defined as its maximal frequency over all possible windows in the stream from any point in the past until the current state that satisfy a minimal length constraint.
Calders, Toon +2 more
openaire +2 more sources
On the Complexity of Mining Itemsets from the Crowd Using Taxonomies [PDF]
, 2013 We study the problem of frequent itemset mining in domains where data is not recorded in a conventional database but only exists in human knowledge. We provide examples of such scenarios, and present a crowdsourcing model for them.
Amarilli, Antoine +2 more
core +2 more sources
A Bitmap Approach for Mining Erasable Itemsets
IEEE Access, 2021 Erasable-itemset mining is a valuable method of pattern extraction for helping the manager of a factory analyze production planning. The erasable itemsets derived can be considered important production information regarding how to plan the production of ...
Tzung-Pei Hong +4 more
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Parallel Algorithm for Frequent Itemset Mining on Intel Many-core Systems [PDF]
, 2018 Frequent itemset mining leads to the discovery of associations and correlations among items in large transactional databases. Apriori is a classical frequent itemset mining algorithm, which employs iterative passes over database combining with generation
Zymbler, Mikhail
core +3 more sources
Multi-Objective Optimization for High-Dimensional Maximal Frequent Itemset Mining
Applied Sciences, 2021 The solution space of a frequent itemset generally presents exponential explosive growth because of the high-dimensional attributes of big data. However, the premise of the big data association rule analysis is to mine the frequent itemset in high ...
Yalong Zhang +4 more
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