Everyday Life Discoveries: Mining and Visualizing Activity Patterns in Social Science Diary Data
2007 (English)In: IEEE International Conference on Information Visualisation,2007: ISSN 1550-6037 / [ed] Ebad Banissi, Remo Aslak Burkhard, Georges Grinstein, Urska Cvek, Marjan Trutschl, Liz Stuart, Theodor G Wyeld, Gennady Andrienko, Jason Dykes, Mikael Jern, Dennis Groth and Anna Ursyn, Los Alamitos, CA, USA: IEEE , 2007, 130-138 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
Los Alamitos, CA, USA: IEEE , 2007. 130-138 p.
, Information Visualization, ISSN 1550-6037
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-40111DOI: 10.1109/IV.2007.48Local ID: 52273ISBN: 0-7695-2900-3OAI: oai:DiVA.org:liu-40111DiVA: diva2:260960
11th International Conference in Information Visualization, 4-6 July, Zürich, Switzerland