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M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 4 Issue 4, April 2015
Mining Frequent Item Set Using Cluster Approach from Large Uncertain Database
Naveen Sarawgi | C. Malathy
Abstract: The data handling in emerging application and technology like sensor systems, location based system and data integration, are often inaccurate and inexact in nature. In this paper we study the extracting of most frequent item set from large size of uncertain database. The main aim of frequent item set mining is to extract useful information and knowledge from uncertain databases. We propose frequent pattern and Fuzzy C-means algorithm. The combination of frequent pattern algorithm and fuzzy c-means algorithm provide fast and accurate mined information.
Keywords: Frequent pattern algorithm, Fuzzy C-means algorithm, uncertain database
Edition: Volume 4 Issue 4, April 2015,
Pages: 1546 - 1551
Similar Articles with Keyword 'uncertain database'
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Dissertation Chapters, Computer Science & Engineering, India, Volume 4 Issue 6, June 2015
Pages: 2953 - 2955Probabilistic Frequent Sequential Patterns Analysis Using Apriori of Unsure Databases
Madhavi G. Patil | Ravi Patki [2]
Downloads: 122
Research Paper, Computer Science & Engineering, India, Volume 3 Issue 4, April 2014
Pages: 409 - 412A Novel Approach on Mining Frequent Item Sets on Large Uncertain Databases
R. Manimegalai | D. Dhanabagyam