Clustering and Query Optimization in Fuzzy Object-Oriented Database

Thuan Tan Nguyen, Ban Van Doan, Chau Ngoc Truong and Trinh Thi Thuy Tran
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Thuan Tan Nguyen: Duy Tan University, Da Nang, Viet Nam
Ban Van Doan: Institute of Information Technology – VAST, Hà Nội, Viet Nam
Chau Ngoc Truong: Information Technology Department – Danang University of Technology, Da Nang, Viet Nam
Trinh Thi Thuy Tran: Information Technology Department – Duy Tan University, Da Nang, Viet Nam

International Journal of Natural Computing Research (IJNCR), 2019, vol. 8, issue 1, 1-17

Abstract: The purpose of the clustering method is to provide some meaningful partitioning of the data set. In general, finding separate clusters with similar members is essential. A problem in clustering is how to determine the number of optimal clusters that best fits the data set. Most clustering algorithms generate a partition based on input parameters (for example, cluster number, minimum density) which results in limiting the number of clusters. Therefore, the article proposes an improved EMC clustering algorithm that is more flexible in handling and manipulating those clusters, where input parameter values are assumed to be different clusters for different partitions of a data set. In addition, based on the above partitioning results, this article proposes a new approach to processing and optimizing fuzzy queries to improve efficiency in the manipulation and processing of specific data such as (less time consuming, less resource consuming)

Date: 2019
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