Abstract—In order to handle imprecise and ambiguous information, the application of fuzzy set theory for the design of database, information storage and retrieval systems has been gaining popularity recently. This paper gives emphasis on the basic characteristics of fuzzy relational databases, their properties, along with the data clustering in database systems. Indian premier league dataset has been considered for the detection of clusters. Several clustering parameters like centroid, radius and Manhattan distance measure have been applied. The definition of clusters as well as the membership function has been implemented using PL/SQL. The results obtained from Indian premier league batting statistics dataset detect two clusters, namely Cluster 1 and Cluster 2. Finally, this article proposed a fuzzy database organization and clustering of records which provides efficient and accurate fuzzy retrieval.
Index Terms—Cluster analysis, fuzzy set theory, data mining, fuzzy relational database, information retrieval.
Pabitra Kumar Dey is with the Department of Computer Application, Dr. B. C Roy Engineering College, Jemua Road, Fuljhore, Durgapur-713206 ,West Bengal, India (e-mail: dey_pabitra@yahoo.co.in)
Gangotri Chakraborty is with the Department of Computer Science, Sikkim Manipal University, India (e-mail: gangotri1986@gmail.com)
Suvobrata Sarkar is with Department of Computer Science and Engineering, Dr. B.C Roy Engineering College, Jemua Road, Fuljhore,Durgapur-713206, West Bengal, India (e-mail: suvobrata.sarkar@ieee.org)
Cite: Pabitra Kumar Dey, Gangotri Chakraborty, and Suvobrata Sarkar, "Cluster Detection Analysis Using Fuzzy Relational Database," International Journal of Information and Electronics Engineering vol. 3, no. 2, pp. 233-236, 2013.