Euclidean co-embedding of ordinal data for multi-type visualization

• Main Authors: LE, Dung D., LAUW, Hady W.
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2016
• 主題: Euclidean; High-dimensional; Information preservation; Low-dimensional representation; Objective metrics; Ordinal data; data visualization; data mining; Databases and Information Systems; Numerical Analysis and Scientific Computing
• 在線閱讀: https://ink.library.smu.edu.sg/sis_research/3358; https://ink.library.smu.edu.sg/context/sis_research/article/4360/viewcontent/EuclideanCo_embedding.pdf
• 機構: Singapore Management University

Embedding deals with reducing the high-dimensional representation of data into a low-dimensional representation. Previous work mostly focuses on preserving similarities among objects. Here, not only do we explicitly recognize multiple types of objects, but we also focus on the ordinal relationships...