Visualizing Bags of Vectors
It addresses the problem of visualizing high-dimensional data for researchers in data analysis, but appears incremental as it builds on existing methods like Minimum Volume Embedding.
This paper compares two methods for visualizing data in bag-of-vectors format and proposes a new theoretical model with sample visualizations to support an alternative visualization mode.
The motivation of this work is two-fold - a) to compare between two different modes of visualizing data that exists in a bag of vectors format b) to propose a theoretical model that supports a new mode of visualizing data. Visualizing high dimensional data can be achieved using Minimum Volume Embedding, but the data has to exist in a format suitable for computing similarities while preserving local distances. This paper compares the visualization between two methods of representing data and also proposes a new method providing sample visualizations for that method.