Conference proceeding
Finding Canonical Behaviors in User Protocols
CHI2009: PROCEEDINGS OF THE 27TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, VOLS 1-4, pp 1323-1326
01 Jan 2009
Abstract
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. The automated method takes advantage of recent algorithmic developments in computational vision, modifying them to allow for distance measures between behavioral protocols. The paper includes an application of the method to web-browsing protocols, showing bow the canonical behaviors found by the method match well to sets of behaviors identified by expert human coders.
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Details
- Title
- Finding Canonical Behaviors in User Protocols
- Creators
- Walter C. Mankowski - Drexel UniversityPeter Bogunovich - Drexel UniversityAli Shokoufandeh - Drexel UniversityDario D. Salvucei - Drexel Univ, Dept Comp Sci, Philadelphia, PA 19104 USA
- Contributors
- S Greenberg (Editor)S E Hudson (Editor)K Hinkley (Editor)M RingelMorris (Editor)D R Olsen (Editor)
- Publication Details
- CHI2009: PROCEEDINGS OF THE 27TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, VOLS 1-4, pp 1323-1326
- Conference
- CHI2009: 27TH ANNUAL CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 27th
- Publisher
- Assoc Computing Machinery
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000265679301016
- Scopus ID
- 2-s2.0-84892447648
- Other Identifier
- 991019170495204721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Computer Science, Theory & Methods
- Information Science & Library Science
- Management
- Social Issues