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Fall 2018 Semester
Dec 18, 2018
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CS 7260 - Visualization for Network Science
Covers the principles of information visualization in the specific context of network science. Introduces visual encoding of data and our understanding of human vision and perception; interaction principles including filtering, pivoting, aggregation; and both quantitative and human subjects evaluation techniques. Covers visualization techniques for several network types, including multivariate networks with attributes for entities and relationships, evolving and dynamic networks that change over time, heterogeneous networks with multiple types of entities, and geospatial networks. Offers students an opportunity to learn about the design of layout algorithms for node-link and matrix visualizations.
4.000 Credit hours
4.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture

Computer Science Department

Course Attributes:
GSCS Computer & Info Science

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

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