Graphs are commonly used visualization tools in a variety of fields. Algorithms have been proposed that claim to improve the readability of graphs by reducing edge crossings, adjusting edge length, or some other means. However, little research has been done to determine which of these algorithms best suit human perception for particular graph properties. This thesis explores four different graph properties: average local clustering coefficient (ALCC), global clustering coefficient (GCC), number of triangles (NT), and diameter.
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- Partial requirement for: M.S., Arizona State University, 2019Note typethesis
- Includes bibliographical references (pages 63-67)Note typebibliography
- Field of study: Computer science