TIFIM: Tree based Incremental Frequent Itemset Mining over Streaming Data
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2013, Vol 10, Issue 5
Abstract
Data Stream Mining algorithms performs under constraints called space used and time taken, which is due to the streaming property. The relaxation in these constraints is inversely proportional to the streaming speed of the data. Since the caching and mining the streaming-data is sensitive, here in this paper a scalable, memory efficient caching and frequent itemset mining model is devised. The proposed model is an incremental approach that builds single level multi node trees called bushes from each window of the streaming data; henceforth we refer this proposed algorithm as a Tree (bush) based Incremental Frequent Itemset Mining (TIFIM) over data streams.
Authors and Affiliations
V. sidda Reddy, Dr T. V. Rao, Dr A. Govardhan
Keywords
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- EP ID EP650205
- DOI 10.24297/ijct.v10i5.4149
- Views 110
- Downloads 0
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