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

How to Cite?: Naveen Sarawgi, C. Malathy, "Mining Frequent Item Set Using Cluster Approach from Large Uncertain Database", Volume 4 Issue 4, April 2015, International Journal of Science and Research (IJSR), Pages: 1546-1551, https://www.ijsr.net/getabstract.php?paperid=SUB153381, DOI: https://dx.doi.org/10.21275/SUB153381