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Extracting sequential frequent itemsets from probabilistic sequences database
Computers now handle large amounts of data, leading to the emergence of data mining as a science to extract useful information from this data....
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Mining frequent Itemsets from transaction databases using hybrid switching framework
With the growing volume of data, mining Frequent Itemsets remains of paramount importance. These have applications in various domains such as market...
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CG-FHAUI: an efficient algorithm for simultaneously mining succinct pattern sets of frequent high average utility itemsets
The identification of both closed frequent high average utility itemsets (CFHAUIs) and generators of frequent high average utility itemsets (GFHAUIs)...
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Hiding sensitive frequent itemsets by item removal via two-level multi-objective optimization
Privacy Preserving Data Mining (PPDM) is an important research area in data mining, which aims at protecting the privacy during the data mining...
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Efficient algorithms for deriving complete frequent itemsets from frequent closed itemsets
When mining frequent itemsets (abbr. FIs ) from dense datasets, it usually produces too many itemsets and results in the mining task to suffer from a...
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Mining Discriminative Itemsets Over Data Streams Using Efficient Sliding Window
In this paper, we present an efficient novel method for mining discriminative itemsets over data streams using the sliding window model....
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Parallel frequent itemsets mining using distributed graphic processing units
Data mining is an essential technique in knowledge discovery which is widely used for pattern extraction and information classification. Extracting...
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Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets
We propose the use of maximal frequent itemsets (MFIs) to derive association rules from tabular datasets. We first present an efficient method to...
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TKU-BChOA: an accurate meta-heuristic method to mine Top-k high utility itemsets
High utility itemset mining is an essential new task in data mining, which is obtained from the extension of frequent itemset mining problems. The...
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High utility itemsets mining from transactional databases: a survey
AbstractMining high utility itemsets are the basic task in the area of frequent itemset mining (FIM) that has various applications in diverse...
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A Review on Frequent Itemsets Generation Techniques and Their Comparative Analysis Using FIMAK
Frequent Itemset Mining (FIM) includes develo** data mining algorithms to discover interesting and productive patterns from a variety of databases....
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Memory-Effective Parallel Mining of Incremental Frequent Itemsets Based on Multi-scale
Frequent Itemset Mining (FIM), as an effective means of discovering related information or knowledge, has high time and space complexity. However, in...
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Hadamard Encoding Based Frequent Itemset Mining under Local Differential Privacy
Local differential privacy (LDP) approaches to collecting sensitive information for frequent itemset mining (FIM) can reliably guarantee privacy....
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Mining Top-K constrained cross-level high-utility itemsets over data streams
Cross-Level High-Utility Itemsets Mining (CLHUIM) aims to discover interesting relationships between hierarchy levels by introducing the taxonomy of...
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An improved frequent pattern tree: the child structured frequent pattern tree CSFP-tree
Frequent itemsets are itemsets that occur frequently in a dataset. Frequent itemset mining extracts specific itemsets with supports higher than or...
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Frequent Pattern
Frequent patterns can be used to characterize a given set of examples: they are the most typical feature combinations in the data. Frequent patterns...
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MFG-HUI: An Efficient Algorithm for Mining Frequent Generators of High Utility Itemsets
The discovery of frequent generators of high utility itemsets (FGHUIs) holds great importance as they provide concise representations of frequent...
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Frequent Itemset
Frequent itemsets are a form of frequent pattern . Given examples that are sets of items and a minimum frequency,...
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GrAFCI+ A fast generator-based algorithm for mining frequent closed itemsets
Mining itemsets for association rule generation is a fundamental data mining task originally stemming from the traditional market basket analysis...
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Efficient Top-k Frequent Itemset Mining on Massive Data
Top- k frequent itemset mining (top- k FIM) plays an important role in many practical applications. It reports the k itemsets with the highest...
