Thesis / Dissertation

Scalable clustering of high dimensional data in non-disjoint axis-parallel subspaces

Minh Tuan Doan, Christopher Leckie (ed.)

Published : 2019

Abstract

Clustering is the task of grouping similar objects together, where each group formed is called a cluster. Clustering is used to discover hidden patterns or underlying structures from the data, and has a wide range of applications in areas such as the Internet of Things (IoT), biology, medicine, marketing, business, and computing. Recent developments in sensor and storage technology have led to a rapid growth of data, both in terms of volume and dimensionality. This raises challenges for existing clustering algorithms and led to the development of subspace clustering algorithms that cope with the characteristics, volumes, and dimensionality of the datasets that are now available. In this thes..

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