Computer Graphics & Visual Computing (CGVC) 2018

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/2632659

Browse

Browsing Computer Graphics & Visual Computing (CGVC) 2018 by Subject "Information visualization"

Now showing 1 - 3 of 3
  • No Thumbnail Available
    Item
    GPU-Assisted Scatterplots for Millions of Call Events
    (The Eurographics Association, 2018) Rees, Dylan; Roberts, Richard C.; Laramee, Robert S.; Brookes, Paul; D'Cruze, Tony; Smith, Gary A.; {Tam, Gary K. L. and Vidal, Franck
    With four percent of the working population employed in call centers in both the United States and the UK, the contact center industry represents a sizable proportion of modern industrial landscapes. As with most modern industries, data collection is de rigueur, producing gigabytes of call records that require analysis. The scatterplot is a well established and understood form of data visualization dating back to the 17th century. In this paper we present an application for visualizing large call centre data sets using hardware-accelerated scatterplots. The application utilizes a commodity graphics card to enable visualization of a month's worth of data, enabling fast filtering of multiple attributes. Filtering is implemented using the Open Computing Language (OpenCL), providing significant performance improvement over traditional methods. We demonstrate the value of our application for exploration and analysis of millions of call events from a real-world industry partner. Domain expert feedback from our industrial partners is reported.
  • No Thumbnail Available
    Item
    RiverState: A Visual Metaphor Representing Millions of Time-Oriented State Transitions
    (The Eurographics Association, 2018) Roberts, Richard C.; Rees, Dylan; Laramee, Robert S.; Brookes, Paul; Smith, Gary A.; {Tam, Gary K. L. and Vidal, Franck
    Developing a positive relationship between a business and its customers is vital to success. The outcome of any customer interaction can determine future patronage of the business. Many industry's only point of interaction with their customers is through a contact centre where everything from sales to complaints are handled. This places tremendous importance on the operational efficiency of the contact centre and the level of care provided to the customers. These customer interactions are recorded and archived in large databases, but undertaking insightful analysis is challenging due to both the size and complexity of the data. We present a visual solution to the tracking of customer interactions at a large scale. RiverState visualises the collective flow of callers through the process of interacting with a contact centre using a river metaphor. We use finite state transition machines with customised edges to depict millions of events and the states callers go through to complete their journey. We implement a range of novel features to enhance the analytical qualities of the application, and collect feedback from domain experts to analyse and evaluate the use of the software.
  • No Thumbnail Available
    Item
    When Size Matters: Towards Evaluating Perceivability of Choropleths
    (The Eurographics Association, 2018) McNabb, Liam; Laramee, Robert S.; Wilson, Max; {Tam, Gary K. L. and Vidal, Franck
    Choropleth maps are an invaluable visualization type for mapping geo-spatial data. One advantage to a choropleth map over other geospatial visualizations such as cartograms is the familiarity of a non-distorted landmass. However, this causes challenges when an area becomes too small in order to accurately perceive the underlying color. When does size matter in a choropleth map? We conduct an experiment to verify the relationship between choropleth maps, their underlying color map, and a user's perceivability. We do this by testing a user's perception of color relative to an administrative area's size within a choropleth map, as well as user-preference of fixed-locale maps with enforced minimum areas. Based on this initial experiment we can make the first recommendations with respect to a unit area's minimum size in order to be perceivably useful.