Visual cluster separation using high-dimensional sharpened dimensionality reduction

IF 1.8 4区计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Information Visualization Pub Date : 2022-04-21 DOI:10.1177/14738716221086589

Youngjoo Kim, Alexandru C Telea, Scott C Trager, Jos BTM Roerdink

引用次数: 0

Abstract

Applying dimensionality reduction (DR) to large, high-dimensional data sets can be challenging when distinguishing the underlying high-dimensional data clusters in a 2D projection for exploratory a...

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基于高维锐化降维的视觉聚类分离

将降维(DR)应用于大型高维数据集，在2D投影中区分潜在的高维数据簇是一项挑战。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Information Visualization COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.40

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Information Visualization is essential reading for researchers and practitioners of information visualization and is of interest to computer scientists and data analysts working on related specialisms. This journal is an international, peer-reviewed journal publishing articles on fundamental research and applications of information visualization. The journal acts as a dedicated forum for the theories, methodologies, techniques and evaluations of information visualization and its applications. The journal is a core vehicle for developing a generic research agenda for the field by identifying and developing the unique and significant aspects of information visualization. Emphasis is placed on interdisciplinary material and on the close connection between theory and practice. This journal is a member of the Committee on Publication Ethics (COPE).