2013 17th International Conference on Information Visualisation (2007)
July 4, 2007 to July 6, 2007
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IV.2007.48
Katerina Vrotsou , Linkoping University, Sweden
Kajsa Ellegard , Linkoping University, Sweden
Matthew Cooper , Linkoping University, Sweden
The ability to identify and examine patterns of activities is a key tool for social and behavioural science. In the past this has been done by statistical or purely visual methods but automated sequential pattern analysis through sophisticated data mining and visualization tools for pattern location and evaluation can open up new possibilities for interactive exploration of the data. This paper describes the addition of a sequential pattern identification method to the visual activity-analysis tool, VISUAL-TimePAcTS, and its effectiveness in the process of pattern analysis in social science diary data. The results have shown that the method correctly identifies patterns and conveys them effectively to the social scientist in a manner that allows them quick and easy understanding of the significance of the patterns.
Katerina Vrotsou, Kajsa Ellegard, Matthew Cooper, "Everyday Life Discoveries: Mining and Visualizing Activity Patterns in Social Science Diary Data", 2013 17th International Conference on Information Visualisation, vol. 00, no. , pp. 130-138, 2007, doi:10.1109/IV.2007.48