liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
ActiviTree: Interactive Visual Exploration of Sequences in Event-Based Data Using Graph Similarity
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.ORCID iD: 0000-0003-4761-8601
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.
Linköping University, Department of Science and Technology, Visual Information Technology and Applications (VITA). Linköping University, The Institute of Technology.
2009 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, ISSN 1077-2626, Vol. 15, no 6, 945-952 p.Article in journal (Refereed) Published
Abstract [en]

The identification of significant sequences in large and complex event-based temporal data is a challenging problem with applications in many areas of todays information intensive society. Pure visual representations can be used for the analysis, but are constrained to small data sets. Algorithmic search mechanisms used for larger data sets become expensive as the data size increases and typically focus on frequency of occurrence to reduce the computational complexity, often overlooking important infrequent sequences and outliers. In this paper we introduce an interactive visual data mining approach based on an adaptation of techniques developed for web searching, combined with an intuitive visual interface, to facilitate user-centred exploration of the data and identification of sequences significant to that user. The search algorithm used in the exploration executes in negligible time, even for large data, and so no pre-processing of the selected data is required, making this a completely interactive experience for the user. Our particular application area is social science diary data but the technique is applicable across many other disciplines.

Place, publisher, year, edition, pages
2009. Vol. 15, no 6, 945-952 p.
Keyword [en]
Interactive visual exploration, event-based data, sequence identification, graph similarity, node similarity
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-51476DOI: 10.1109/TVCG.2009.117OAI: diva2:275286
Available from: 2009-11-04 Created: 2009-11-04 Last updated: 2015-03-25
In thesis
1. Everyday mining: Exploring sequences in event-based data
Open this publication in new window or tab >>Everyday mining: Exploring sequences in event-based data
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Utforskning av sekvenser i händelsebaserade data
Abstract [en]

Event-based data are encountered daily in many disciplines and are used for various purposes. They are collections of ordered sequences of events where each event has a start time and a duration. Examples of such data include medical records, internet surfing records, transaction records, industrial process or system control records, and activity diary data.

This thesis is concerned with the exploration of event-based data, and in particular the identification and analysis of sequences within them. Sequences are interesting in this context since they enable the understanding of the evolving character of event data records over time. They can reveal trends, relationships and similarities across the data, allow for comparisons to be made within and between the records, and can also help predict forthcoming events.The presented work has researched methods for identifying and exploring such event-sequences which are based on modern visualization, interaction and data mining techniques.

An interactive visualization environment that facilitates analysis and exploration of event-based data has been designed and developed, which permits a user to freely explore different aspects of this data and visually identify interesting features and trends. Visual data mining methods have been developed within this environment, that facilitate the automatic identification and exploration of interesting sequences as patterns. The first method makes use of a sequence mining algorithm that identifies sequences of events as patterns, in an iterative fashion, according to certain user-defined constraints. The resulting patterns can then be displayed and interactively explored by the user.The second method has been inspired by web-mining algorithms and the use of graph similarity. A tree-inspired visual exploration environment has been developed that allows a user to systematically and interactively explore interesting event-sequences.Having identified interesting sequences as patterns it becomes interesting to further explore how these are incorporated across the data and classify the records based on the similarities in the way these sequences are manifested within them. In the final method developed in this work, a set of similarity metrics has been identified for characterizing event-sequences, which are then used within a clustering algorithm in order to find similarly behavinggroups. The resulting clusters, as well as attributes of the clusteringparameters and data records, are displayed in a set of linked views allowing the user to interactively explore relationships within these.

The research has been focused on the exploration of activity diary data for the study of individuals' time-use and has resulted in a powerful research tool facilitating understanding and thorough analysis of the complexity of everyday life.

Place, publisher, year, edition, pages
Norrköping: Linköping University Electronic Press, 2010. 76 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1331
Event-based data, activity diary data, event-sequences, interactive exploration, sequence identification, visual data mining
National Category
Computer Science
urn:nbn:se:liu:diva-58311 (URN)978-91-7393-343-8 (ISBN)
Public defence
2010-09-10, Domteater, Norrköpings Visualiseringscenter C, Kungsgatan 54, 602 33 Norrköping, 09:15 (English)
Available from: 2010-09-01 Created: 2010-08-10 Last updated: 2015-09-22Bibliographically approved

Open Access in DiVA

fulltext(3845 kB)47 downloads
File information
File name FULLTEXT01.pdfFile size 3845 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Search in DiVA

By author/editor
Vrotsou, KaterinaJohansson, JimmyCooper, Matthew
By organisation
Visual Information Technology and Applications (VITA)The Institute of Technology
In the same journal
IEEE Transactions on Visualization and Computer Graphics
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 47 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 128 hits
ReferencesLink to record
Permanent link

Direct link