TY - GEN
T1 - The CLOTHO project
T2 - 8th ACM Conference on Designing Interactive Systems, DIS 2010
AU - Hailpern, Joshua
AU - Jitkoff, Nicholas
AU - Subida, Joseph
AU - Karahalios, Karrie
PY - 2010
Y1 - 2010
N2 - When using the computer, each user has some notion that "these applications are important" at a given point in time. We term this subset of applications that the user values as high-utility applications. Identifying high-utility applications is a critical first step for Task Analysis, Time Management/Workflow analysis, and Interruption research. However, existing techniques fail to identify at least 57% of these applications. Our work directly associates measurable computer interaction (CPU consumption, window area, etc.) with the user's perceived application utility without identifying task. In this paper, we present an objective utility function that accurately predicts the user's subjective impressions of application importance, improving existing techniques by 53%. This model of computer usage is based upon 321 hours of real-world data from 22 users (both professional and academic). Unlike existing approaches, our model is not limited by a pre-existing set of applications or known tasks. We conclude with a discussion of the direct implications for improving accuracy in the fields of interruptions, task analysis, and time management systems.
AB - When using the computer, each user has some notion that "these applications are important" at a given point in time. We term this subset of applications that the user values as high-utility applications. Identifying high-utility applications is a critical first step for Task Analysis, Time Management/Workflow analysis, and Interruption research. However, existing techniques fail to identify at least 57% of these applications. Our work directly associates measurable computer interaction (CPU consumption, window area, etc.) with the user's perceived application utility without identifying task. In this paper, we present an objective utility function that accurately predicts the user's subjective impressions of application importance, improving existing techniques by 53%. This model of computer usage is based upon 321 hours of real-world data from 22 users (both professional and academic). Unlike existing approaches, our model is not limited by a pre-existing set of applications or known tasks. We conclude with a discussion of the direct implications for improving accuracy in the fields of interruptions, task analysis, and time management systems.
KW - application importance
KW - application utility
KW - interruptions
KW - modeling
KW - task analysis
KW - workflow analysis
UR - http://www.scopus.com/inward/record.url?scp=78149319142&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78149319142&partnerID=8YFLogxK
U2 - 10.1145/1858171.1858230
DO - 10.1145/1858171.1858230
M3 - Conference contribution
AN - SCOPUS:78149319142
SN - 9781450301039
T3 - DIS 2010 - Proceedings of the 8th ACM Conference on Designing Interactive Systems
SP - 330
EP - 339
BT - DIS 2010 - Proceedings of the 8th ACM Conference on Designing Interactive Systems
Y2 - 16 August 2010 through 20 August 2010
ER -