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Mining Closed Frequent Itemsets in Sliding Window over Data Streams
- Source :
- 2008 3rd International Conference on Innovative Computing Information and Control.
- Publication Year :
- 2008
- Publisher :
- IEEE, 2008.
-
Abstract
- As one of the most important problems in data streams mining, many studies have been done on mining closed frequent itemsets. However mining closed frequent itemsets in data streams has not been well addressed. In this paper, we design HCI-Mtree (Hash-based Closed Itemsets Monolayer tree) to maintain the complete set of current closed itemsets. In HCI-Mtree, the itemsets with the same frequency are linked to the same hash-based counter. To mining closed frequent itemsets in sliding window over data streams, we propose a novel approach HCFI (algorithm based on HCI-Mtree for mining Closed Frequent Itemsets). Vertical representation of transactions is utilized in our algorithm to save processing time and space consuming. Our experiments show that HCFI has good performance especially when the window size is large.
- Subjects :
- Data stream mining
Computer science
Group method of data handling
Hash function
InformationSystems_DATABASEMANAGEMENT
Data structure
computer.software_genre
Set (abstract data type)
Tree (data structure)
ComputingMethodologies_PATTERNRECOGNITION
Sliding window protocol
Algorithm design
Data mining
computer
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2008 3rd International Conference on Innovative Computing Information and Control
- Accession number :
- edsair.doi...........5909c508921618c00fb53c161f6e7069