activity
20162021
most citedRevisiting Dimensionality Reduction Techniques for Visual Cluster Analysis: An Empirical Study

84 citations · 164 across the 8 of their papers we have counts for

collaborators

13 papers

cs.HC202184 cited

Revisiting Dimensionality Reduction Techniques for Visual Cluster Analysis: An Empirical Study

Jiazhi Xia, Yuchen Zhang, Jie Song +3

Dimensionality Reduction (DR) techniques can generate 2D projections and enable visual exploration of cluster structures of high-dimensional datasets. However, different DR techniq…

cs.HC2021

Real-Time Visual Analysis of High-Volume Social Media Posts

Johannes Knittel, Steffen Koch, Tan Tang +4

Breaking news and first-hand reports often trend on social media platforms before traditional news outlets cover them. The real-time analysis of posts on such platforms can reveal…

cs.LG202054 cited

Interactive Steering of Hierarchical Clustering

Weikai Yang, Xiting Wang, Jie Lu +2

Hierarchical clustering is an important technique to organize big data for exploratory data analysis. However, existing one-size-fits-all hierarchical clustering methods often fail…

cs.SI2020

Preserving Minority Structures in Graph Sampling

Ying Zhao, Haojin Jiang, Qi'an Chen +6

Sampling is a widely used graph reduction technique to accelerate graph computations and simplify graph visualizations. By comprehensively analyzing the literature on graph samplin…

cs.HC202013 cited

A Survey of Visual Analytics Techniques for Machine Learning

Jun Yuan, Changjian Chen, Weikai Yang +3

Visual analytics for machine learning has recently evolved as one of the most exciting areas in the field of visualization. To better identify which research topics are promising a…

cs.HC20206 cited

OoDAnalyzer: Interactive Analysis of Out-of-Distribution Samples

Changjian Chen, Jun Yuan, Yafeng Lu +4

One major cause of performance degradation in predictive models is that the test samples are not well covered by the training data. Such not well-represented samples are called OoD…