Within linguistics, the use of large sets of data via a combination of rule-based and stochastic methods is now standardly part of the analysis of language structure. However, though scatter plots, bar or pie charts, and trees as provided by R, for example, are standardly used, novel visual computation techniques have only just begun to be explored. The overall aim of this project is to evaluate whether visual analytics indeed represents a methodology that can yield improved results for linguistic research and to establish metrics for the evaluation of visual analytics approaches by conducting linguistically motivated case studies on historical data.
What visual variables and representations are most effective for which problems?
Which metrics for evaluation can be established?
What visual variables and representations are most effective for which problems?
Can visual analytic methods yield improved results within linguistic research?
Can we find linguistic patterns/insights we could not have found without visual analytics?
Can we find patterns/insights more quickly with visual analytics than without?
Models and Measures
Completed
Adaptive Algorithms
Completed
Interaction
Completed
Applications
Completed
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