A formal series-based unification of the frequent itemset mining approaches
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DOI: 10.1007/s10115-017-1048-y
Abstract: Over the last two decades, a great deal of work has been devoted to the algorithmic aspects of the frequent itemset (FI) mining problem, leading to a phenomenal number of algorithms and associated implementations, each… read more here.
Keywords: itemset mining; mining; frequent itemset; formal series ... See more keywords
Approximation of Probabilistic Maximal Frequent Itemset Mining Over Uncertain Sensed Data
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DOI: 10.1109/access.2020.2997409
Abstract: Event detection by discovering frequent itemsets is very popular in sensor network communities. However, the recorded data is often a probability rather than a determined value in a really productive environment as sensed data is… read more here.
Keywords: tex math; frequent itemset; maximal frequent; sensed data ... See more keywords
Storage Location Assignment Heuristics Based on Slot Selection and Frequent Itemset Grouping for Large Distribution Centers
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DOI: 10.1109/access.2020.3031585
Abstract: This paper considers heuristic approaches that can be used to assign stock keeping units (SKU) to individual slots in distribution center. Firstly, we propose two novel strategies, slot selection and frequent itemset grouping. The former… read more here.
Keywords: slot selection; itemset grouping; frequent itemset; distribution ... See more keywords
The combination of term relations analysis and weighted frequent itemset model for multidocument summarization
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DOI: 10.1111/coin.12270
Abstract: Nowadays, it is necessary that users have access to information in a concise form without losing any critical information. Document summarization is an automatic process of generating a short form from a document. In itemset‐based… read more here.
Keywords: multidocument summarization; term; frequent itemset; summarization ... 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
An Efficient Spark-Based Hybrid Frequent Itemset Mining Algorithm for Big Data
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DOI: 10.3390/data7010011
Abstract: Frequent itemset mining (FIM) is a common approach for discovering hidden frequent patterns from transactional databases used in prediction, association rules, classification, etc. Apriori is an FIM elementary algorithm with iterative nature used to find… read more here.
Keywords: spark; frequent itemset; itemset mining; spark based ... See more keywords