Optimizing Query Results Integration Process Using an Extended Fuzzy C-Means Algorithm

Naoual Mouhni, Abderrafiaa Elkalay, Mohamed Chakraoui

University Cadi Ayyad , Marrakesh, Morocco.

DOI: 10.4236/jsea.2014.75032                

Abstract

Cleaning duplicate data is a major problem that persists even though many works have been done to solve it, due to the exponential growth of data amount treated and the necessity to use scalable and speed algorithms. This problem depends on the type and quality of data, and differs according to the volume of data set manipulated. In this paper we are going to introduce a novel framework based on extended fuzzy C-means algorithm by using topic ontology. This work aims to improve the OLAP querying process over heterogeneous data warehouses that contain big data sets, by improving query results integration, eliminating redundancies by using the extended classification algorithm, and measuring the loss of information.

Keywords

Clustering, Classification and Association Rules, Database Integration, Data Warehouse and Repository, Heterogeneous Databases, Query Processing

Conflicts of Interest

The authors declare no conflicts of interest.

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