NDLI: Network-Based Clustering and Embedding for High-Dimensional Data Visualization

Content Provider	IEEE Xplore Digital Library
Author	Hengyuan Zhang Xiaowu Chen
Copyright Year	2013
Description	Author affiliation: Sch. of Comput. Sci. & Eng., Beihang Univ., Beijing, China (Hengyuan Zhang; Xiaowu Chen)
Abstract	We present a novel method to visualize high-dimensional dataset as a landscape. The goal is to provide clear and compact representation to reveal the structure of high-dimensional datasets in a way that the size and distinctiveness of clusters can be easily discerned, and the relationships among single points can be preserved. Our method is network-based, and consists of two main steps: clustering and embedding. First of all, the similarity graph of high-dimensional dataset is constructed based on the Euclidean distances between data points. For clustering, we propose a new network community detection algorithm to calculate the membership-degree of each vertex belonging to each community. For embedding, we bring forward a practical algorithm to obtain an evenly distributed and regularly shaped layout of data points, in a way that the original relationships among single points are preserved. Finally, the landscape-like visualization is produced by assigning altitudes to data points according to their membership-degrees and by inserting control points. In our high-dimensional data visualization, clusters form highlands, and border data points among clusters show up as valleys. The area and altitude of highland indicate the size and distinctiveness of data cluster respectively.
Starting Page	290
Ending Page	297
File Size	3772382
Page Count	8
File Format	PDF
ISBN	9781479925766
DOI	10.1109/CADGraphics.2013.45
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	High-dimensional data Visualization Shape Fuzzy clustering Social network services Communities Data visualization Clustering algorithms Network Embedding Partitioning algorithms Springs
Content Type	Text
Resource Type	Article

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