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Dissertation
Canonical behavior patterns
Doctor of Philosophy (Ph.D.), Drexel University
Jun 2012
DOI:
https://doi.org/10.17918/etd-3850
Abstract
A common problem in many areas of behavioral research is the analysis of the large volume of protocol data recorded during the execution of tasks. This dissertation describes a new automated method of protocol analysis to find canonical behaviors: a small subset of behavior protocols that are most representative of the full data set. The method I have developed takes advantage of recent algorithmic developments in pattern recognition. By adapting these methods to the analysis of behavior protocols, I provide a new tool for analysts working with large datasets that are infeasible to study using current methods. The method I propose can also be used as an important complement to existing sequential protocol analysis techniques, by allowing researchers to build their models based on a few highly representative samples. The contributions of this dissertation include the adaptation of the method to the analysis of behavior protocols; the development of similarity measures appropriate to behavior protocols; an extension of the method to work in oriented topologies; and a demonstration of the method's utility in real-world problem domains, particularly web browsing and driving.
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Details
- Title
- Canonical behavior patterns
- Creators
- Walter C. Mankowski - DU
- Contributors
- Dario D. Salvucci (Advisor) - Drexel University (1970-)Ali Shokoufandeh (Advisor) - Drexel University (1970-)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- College of Arts and Sciences; Drexel University; Mathematics
- Other Identifier
- 3850; 991014632263004721