Massive amount of movement data, such as daily trips made by millions of passengers in a
city, are widely available nowadays. They are a highly valuable means not only for unveiling …

We present a set of interactive techniques for the visual analysis of multi‐dimensional
categorical data. Our approach is based on multiple correspondence analysis (MCA), which …

Contingency tables summarize the relations between categorical variables and arise in both
scientific and business domains. Asymmetrically large two-way contingency tables pose a …

Chord diagrams are a popular high-dimensional method for showing connections between
nodes, however they have scalability limitations and lack advanced methods for interaction …

We present a visual analytics solution designed to address prevalent issues in the area of
Operational Decision Management (ODM). In ODM, which has its roots in Artificial …

A wide variety of real-world applications generate massive high dimensional categorical
datasets. These datasets contain categorical variables whose values comprise a set of …

Latent Semantic Indexing (LSI) is an advanced method widely and successfully employed in
Information Retrieval (IR). It is an extension of Vector Space Model (VSM) and it is able to …

We introduce CatNetVis, a novel method of representing semantical relations in categorical
high-dimensional data. Traditional methods provide insights into many aspects of visual …

Analysts are often interested in understanding the association between variables within a
dataset. This paper describes a set of techniques for augmenting the Heatmap Matrix, which …

Abstract The Dot-Based Contingency Wheel is an interactive visual-analytics method
designed to discover and analyze positive associations in an asymmetrically large n× m …