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Paper Details
Paper Title
A Review Paper on Frequent Pattern Mining with Uncertain Data
Authors
  Sapna Saparia,  Prof. Madhushree B
Abstract
There are too many existing algorithms proposed that mines frequent patterns from certain or precise data. But now a day's requirement of uncertain data mining is increased. There are plenty of real world situations in which data are uncertain where mining is required. For frequent pattern mining from uncertain data mainly two approaches are proposed that are step-by-step approach and pattern-growth approach. Level-wise approach use to generate and test strategy. U-Apriori algorithm is the example of step-by-step approach. Pattern-growth approach uses tree like format structure. UF-growth algorithm, UFP-growth algorithm, CUFP-mine algorithm, PUF-growth algorithm are the real world example of pattern-growth approach. Here we are taking the survey of algorithms that are used to mine frequent patterns from uncertain data to maintain the data generated from real world applications.
Keywords- Frequent Pattern Mining, Data Mining Algorithms, Expected Support, Frequent Patterns, Tree Structures, and Uncertain Data
Publication Details
Unique Identification Number - IJEDR1504121Page Number(s) - 704-709Pubished in - Volume 3 | Issue 4 | December 2015DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Sapna Saparia,  Prof. Madhushree B,   "A Review Paper on Frequent Pattern Mining with Uncertain Data", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 4, pp.704-709, December 2015, Available at :http://www.ijedr.org/papers/IJEDR1504121.pdf
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