On mining approximate and exact fault-tolerant frequent itemsets
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DOI: 10.1007/s10115-017-1079-4
Abstract: Robust frequent itemset mining has attracted much attention due to the necessity to find frequent patterns from noisy data in many applications. In this paper, we focus on a variant of robust frequent itemsets in… read more here.
Keywords: fault tolerant; exact fault; mining approximate; frequent itemsets ... See more keywords
TDUP: an approach to incremental mining of frequent itemsets with three-way-decision pattern updating
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DOI: 10.1007/s13042-015-0337-6
Abstract: Finding an efficient approach to incrementally update and maintain frequent itemsets is an important aspect of data mining. Earlier incremental algorithms focused on reducing the number of scans of the original database while it is… read more here.
Keywords: mining; three way; frequent itemsets; way decision ... See more keywords
Knowledge acquisition of association rules from the customer-lifetime-value perspective
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DOI: 10.1108/k-03-2016-0042
Abstract: Customer lifetime value (CLV) scoring is highly effective when applied to marketing databases. Some researchers have extended the traditional association rule problem by associating a weight with each item in a transaction. However, studies of… read more here.
Keywords: lifetime value; association rules; customer lifetime; association ... See more keywords
A Fast Approach for Up-Scaling Frequent Itemsets
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DOI: 10.1109/access.2020.2995719
Abstract: With the rapid growth of data scale and diversification of demand, people have an urgent desire to extract useful frequent itemset from datasets of different scales. It is no doubt that the traditional method can… read more here.
Keywords: scaling frequent; fast approach; approach scaling; frequent itemsets ... See more keywords
Efficient Mining of Frequent Itemsets Using Only One Dynamic Prefix Tree
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DOI: 10.1109/access.2020.3029302
Abstract: Frequent itemset mining is a fundamental problem in data mining area because frequent itemsets have been extensively used in reasoning, classifying, clustering, and so on. To mine frequent itemsets, previous algorithms based on a prefix… read more here.
Keywords: frequent itemsets; mining; dynamic prefix; prefix ... See more keywords
Finding Stable Periodic-Frequent Itemsets in Big Columnar Databases
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DOI: 10.1109/access.2023.3241313
Abstract: Stable periodic-frequent itemset mining is essential in big data analytics with many real-world applications. It involves extracting all itemsets exhibiting stable periodic behaviors in a temporal database. Most previous studies focused on finding these itemsets… read more here.
Keywords: database; periodic frequent; columnar databases; frequent itemsets ... See more keywords
The Mining Algorithm of Maximum Frequent Itemsets Based on Frequent Pattern Tree
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DOI: 10.1155/2022/7022168
Abstract: In the discipline of data mining, association rule mining is an important study topic that focuses on discovering the relationships between database attributes. The maximum frequent itemset comprises the information of all frequent itemsets, which… read more here.
Keywords: maximum frequent; pattern tree; frequent pattern; frequent itemset ... See more keywords
Towards Scalable Algorithm for Closed Itemset Mining in High-Dimensional Data
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DOI: 10.11591/ijeecs.v8.i2.pp487-494
Abstract: Mining frequent itemsets from large dataset has a major drawback in which the explosive number of itemsets requires additional mining process which might filter the interesting ones. Therefore, as the solution, the concept of closed… read more here.
Keywords: high dimensional; mining; dimensional data; scalable algorithm ... See more keywords