Research Projects

ReCloud: Semantics-Based Word Cloud Visualization of User Reviews

User reviews, like those found on Yelp and Amazon, have become an important reference for decision making in daily life, for example, in dining, shopping and entertainment. However, large amounts of available reviews make the reading process tedious. Existing word cloud visualizations attempt to provide an overview. However their randomized layouts do not reveal content relationships to users. In this paper, we present ReCloud, a word cloud visualization of user reviews that arranges semantically related words as spatially proximal.

InfoVis Taxomony:

ForceSpire: Semantic Interaction for Visual Analytics

This section describes our work on Semantic Interaction, a design space for user interaction in visual analytic tools that infer analytic reasoning of users for model steering.

InfoVis Taxomony:

Analyst Workspace: An Embodied Sensemaking Environment for Large, High-Resolution Displays

Distributed cognition and embodiment provide compelling models for how humans think and interact with the environment. Our examination of the use of large, high-resolution displays from an embodied perspective has lead directly to the development of a new sensemaking environment called Analyst’s Workspace (AW). AW leverages the embodied resources made more accessible through the physical nature of the display to create a spatial workspace.

InfoVis Taxomony:

Inspecting and Visualizing High-fidelity Terrain Data with Large-High Resolution Displays

The Vehicle Terrain Measurement System (VTMS) allows highly detailed terrain modeling and vehicle simulations. Visualization of large-scale terrain datasets taken from VTMS provides insights into the characteristics of the pavement or road surface. However, the resolution of these terrain datasets greatly exceeds the capability of traditional graphics displays and computer systems.

InfoVis Taxomony:

BaVA: Bayesian Visual Analytics

The goal of this project is to enable end users to directly manipulate data visualizations created by mathematical models for dimension reduction. Users can explore structure in high-dimensional data by directly moving data points within the visualization, causing the models to learn from the user feedback, and viewing the effects of those movements on other points.
Also known as Object-Level Interaction (OLI) and Visual-to-Parametric Interaction (V2PI).
See also Semantic Interaction.

VisPorter: Visual Analytics for Display Ecology

The multiplicity of computing and display devices currently available presents new opportunities for how visual analytics is performed. One of the significant inherent challenges that comes with the use of multiple and varied types of displays for visual analytics is sharing and subsequent integration of information among different devices. Multiple devices enable analysts to employ and extend visual space for working with visualizations, but it requires users to switch intermittently between activities and foci of interest over different workspaces.

InfoVis Taxomony:

VizCept: Supporting Synchronous Collaboration for Constructing Visualizations in Intelligence Analysis

VizCept is a new web-based visual analytics system which is designed to support fluid, collaborative analysis of large textual intelligence datasets. The main approach of the design is to combine individual workspace and shared visualization in an integrated environment. Collaborating analysts will be able to identify concepts and relationships from the dataset based on keyword searches in their own workspace and collaborate visually with other analysts using visualization tools such as a concept map view and a timeline view.

InfoVis Taxomony:

Clustered Layout Word Cloud for User Generated Online Reviews

User generated reviews, like those found on Yelp and Amazon, have become important reference material in casual decision making, like dining, shopping and entertainment. However, very large amounts of reviews make the review reading process time consuming. A text visualization can speed up the review reading process.

InfoVis Taxomony:

Information Salience

Large collections of documents create a cumbersome comprehension task. To lighten the load, interactive computational techniques can create visual summaries of these documents. We conducted a study comparing document highlights from humans to document highlights from a salience algorithm. We are exploring interactive computational techniques identified from the study results as well as the modified salience algorithm within an interactive tool. We developed a salience tool that visualizes highlights based on percentages of users who found sentences salient.

InfoVis Taxomony:

Insight-based Evaluation

Insight-based evaluation is a method to evaluate visualizations by measuring the amount and type of insight they produce. The goal is to move beyond standard measures of time and accuracy to better reflect the true purpose of visualization -- insight.

http://infovis.cs.vt.edu/search/node/saraiya%20OR%20insight

InfoVis Taxomony:

Keywords:

Pages

Subscribe to Research Projects