Fuzzy Databases Using Extended Fuzzy C-Means Clustering

In recent years, the Fuzzy Relational Database and its queries have gradually become a new research topic. Fuzzy Structured Query Language (FSQL) is used to retrieve the data from fuzzy database because traditional Structured Query Language (SQL) is inefficient to handling uncertain and vague queries. The proposed model provides the facility for naïve users for retrieving relevant results of non-crisp queries and improves the relevance of results provided by Fuzzy C-Means (FCM) through the use of extended Fuzzy C-Means (EFCM). An extended fuzzy clustering algorithm based on the Gustafson-Kessel (GK) algorithm. Fuzzy C-Means and Gustafson-Kessel algorithm both are well known fuzzy clustering algorithms. Gustafson-Kessel algorithm is needed because the clustering results of the traditional Fuzzy C-Means clustering algorithm are less stable and all the clusters are spherical shaped only. GustafsonKessel algorithm is useful for making clusters of different geometrical shapes. The result analysis of both the algorithms is on the basis of cluster validity measures which indicate that Gustafson-Kessel algorithm is better than Fuzzy C-Means fuzzy clustering algorithm.