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M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 4 Issue 4, April 2015 | Rating: 6.3 / 10
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