Searching for "Approximation of Frequent Itemsets." – sorted by Relevance.
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Mining Approximate Frequent Itemset from Noisy Data
- Mining Approximate Frequent Itemsets from Noisy Data 1 Jinze Liu, 1 Susan Paulsen, 1 Wei Wang, 1
- Cited by 2 (2 self) – Add To MetaCart
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Mining approximate frequent itemsets in the presence of noise: Algorithm and analysis
- Mining Approximate Frequent Itemsets In the Presence of Noise: Algorithm and Analysis 1 Jinze Liu
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Approximation of frequency queries by means of free-sets
- to approximate the support of any frequent itemset. Experiments run on real dense data sets show a significant
- Cited by 50 (21 self) – Add To MetaCart
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AC-Close: efficiently mining approximate closed itemsets by core pattern recovery
- . To tackle such a problem, we propose to recover the approximate frequent itemsets from “core patterns
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Succinct Summarization of Transactional Databases: An Overlapped Hyperrectangle Scheme
- positive assumption (we consider both). Approximate Frequent Itemset Mining: Mining error-tolerant frequent
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Significance and recovery of block structures in binary matrices with noise
- of additive noise using an error-tolerant criterion (approximate frequent itemsets) that allows submatrices
- Cited by 4 (1 self) – Add To MetaCart
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Mining Approximate Order Preserving Clusters in the Presence of Noise
- the same pattern. Beside the strict models, we also review the work of approximate frequent itemset mining
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Dense Itemsets
- . This definition leads to two problems: first, any frequent itemset will generate many approximately frequent
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Discovering Frequent Itemsets in the Presence of Highly Frequent Items
- purposes. 4.1 Approximating Con dence Once the frequent itemsets have been discovered, further e ort must
- Cited by 3 (1 self) – Add To MetaCart
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Transaction databases, frequent itemsets, and their condensed representations
- this difficulty. For example, a simple approximation of frequencies of the frequent itemsets can be obtained
- Cited by 1 (1 self) – Add To MetaCart

