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A survey of itemset mining
Itemset mining is an important subfield of data mining, which consists of discovering
interesting and useful patterns in transaction databases. The traditional task of frequent …
interesting and useful patterns in transaction databases. The traditional task of frequent …
Algorithms for frequent itemset mining: a literature review
Data Analytics plays an important role in the decision making process. Insights from such
pattern analysis offer vast benefits, including increased revenue, cost cutting, and improved …
pattern analysis offer vast benefits, including increased revenue, cost cutting, and improved …
High utility itemset mining with techniques for reducing overestimated utilities and pruning candidates
High utility itemset mining considers the importance of items such as profit and item
quantities in transactions. Recently, mining high utility itemsets has emerged as one of the …
quantities in transactions. Recently, mining high utility itemsets has emerged as one of the …
Top-k high utility pattern mining with effective threshold raising strategies
In pattern mining, users generally set a minimum threshold to find useful patterns from
databases. As a result, patterns with higher values than the user-given threshold are …
databases. As a result, patterns with higher values than the user-given threshold are …
A survey of pattern mining in dynamic graphs
Graph data is found in numerous domains such as for the analysis of social networks,
sensor networks, bioinformatics, industrial systems, and chemistry. Analyzing graphs to …
sensor networks, bioinformatics, industrial systems, and chemistry. Analyzing graphs to …
High utility pattern mining over data streams with sliding window technique
Processing changeable data streams in real time is one of the most important issues in the
data mining field due to its broad applications such as retail market analysis, wireless sensor …
data mining field due to its broad applications such as retail market analysis, wireless sensor …
DiffNodesets: An efficient structure for fast mining frequent itemsets
Mining frequent itemsets is an essential problem in data mining and plays an important role
in many data mining applications. In recent years, some itemset representations based on …
in many data mining applications. In recent years, some itemset representations based on …
A scalable association rule learning heuristic for large datasets
Many algorithms have proposed to solve the association rule learning problem. However,
most of these algorithms suffer from the problem of scalability either because of tremendous …
most of these algorithms suffer from the problem of scalability either because of tremendous …
A new efficient approach for mining uncertain frequent patterns using minimum data structure without false positives
The concept of uncertain pattern mining was recently proposed to fulfill the demand for
processing databases with uncertain data, and various relevant methods have been …
processing databases with uncertain data, and various relevant methods have been …
Incremental high utility pattern mining with static and dynamic databases
Pattern mining is a data mining technique used for discovering significant patterns and has
been applied to various applications such as disease analysis in medical databases and …
been applied to various applications such as disease analysis in medical databases and …