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While the collection of behavioral protocols has been common practice in human-computer interaction research for many years, the analysis of large protocol data sets is often extremely tedious and time-consuming, and automated analysis methods have been slow to develop. This paper proposes an automated method of protocol analysis to find canonical behaviors - a small subset of protocols that is most representative of the full data set, providing a reasonable "Big picture" view of the data with as few protocols as possible.
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