[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.33851/JMIS.2019.6.1.37

A Study on Representative Skyline Using Connected Component Clustering

Choi, Jong-Hyeok (Dept. of Computer Science, Chungbuk National University)
Nasridinov, Aziz (Dept. of Computer Science, Chungbuk National University)

Publication Information

Journal of Multimedia Information System / v.6, no.1, 2019 , pp. 37-42 More about this Journal

Abstract

Skyline queries are used in a variety of fields to make optimal decisions. However, as the volume of data and the dimension of the data increase, the number of skyline points increases with the amount of time it takes to discover them. Mainly, because the number of skylines is essential in many real-life applications, various studies have been proposed. However, previous researches have used the k-parameter methods such as top-k and k-means to discover representative skyline points (RSPs) from entire skyline point set, resulting in high query response time and reduced representativeness due to k dependency. To solve this problem, we propose a new Connected Component Clustering based Representative Skyline Query (3CRS) that can discover RSP quickly even in high-dimensional data through connected component clustering. 3CRS performs fast discovery and clustering of skylines through hash indexes and connected components and selects RSPs from each cluster. This paper proves the superiority of the proposed method by comparing it with representative skyline queries using k-means and DBSCAN with the real-world dataset.

Keywords

Skyline queries; Representative skyline queries; Density-based clustering; Hash index;

Citations & Related Records

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