Sequence mining in categorical domains: incorporating constraints
Proceedings of the ninth international conference on Information and knowledge management
Extracting usability information from user interface events
ACM Computing Surveys (CSUR)
Work rhythms: analyzing visualizations of awareness histories of distributed groups
CSCW '02 Proceedings of the 2002 ACM conference on Computer supported cooperative work
Kernel Principal Component Analysis
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
Making sense of low-level usage data to understand user activities
SAICSIT '04 Proceedings of the 2004 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries
Comparing episodic and semantic interfaces for task boundary identification
CASCON '07 Proceedings of the 2007 conference of the center for advanced studies on Collaborative research
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Working Overtime: Patterns of Smartphone and PC Usage in the Day of an Information Worker
Pervasive '09 Proceedings of the 7th International Conference on Pervasive Computing
Real-time detection of task switches of desktop users
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Constructing comprehensive summaries of large event sequences
ACM Transactions on Knowledge Discovery from Data (TKDD)
Temporal task footprinting: identifying routine tasks by their temporal patterns
Proceedings of the 15th international conference on Intelligent user interfaces
Approaching process mining with sequence clustering: experiments and findings
BPM'07 Proceedings of the 5th international conference on Business process management
An algorithmic approach to event summarization
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
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This paper proposes a novel method for analyzing PC usage logs aiming to find working patterns and behaviors of employees at work. The logs we analyze are recorded at individual PCs for employees in a company, and include active window transitions. Our method consists of two levels of abstraction: (1) task summarization by HMM; (2) user behavior comparison by kernel principle component analysis based on a graph kernel. The experimental results show that our method reveals implicit user behavior at a high level of abstraction, and allows us to understand individual user behavior among groups, and over time.