Abstract
Research Area: Information visualization, human-computer interaction.
Research Topic. The main research topic of the thesis is to explore the possibilities of automated clustering and machine learning techniques for developing new approaches in information visualization.
Research Problem. The main goal of information visualization is to present data to the users in a way that optimizes intelligibility of the data and support the detection of relevant patterns in the data, where the application context defines what qualifies as ‘relevant’. Many different approaches typically tailored to a specific problem have been developed within the past years. At the same time the application of mathematical methods for data analysis and identification of patterns has substantially increased, and is typically referred to as data mining. Different visualization techniques are used in data mining, however the systematic and dynamic integration of data mining techniques with visualization approaches is only in its beginning.
Advisor: Prof. Manfred Tscheligi manfred.tscheligi@sbg.ac.at
Chapter PDF
Similar content being viewed by others
References
Fujimura, K., Fujimura, S., Matsubayashi, T., Yamada, T., Okuda, H.: Topigraphy: visualization for large-scale tag clouds. In: Proc. WWW 2008 (2008)
Hassan-Montero, Y., Herrero-Solana, V.: Improving tagclouds as visual information retrieval interfaces. In: Proc. InfoSciT 2006 (2006)
Lohmann, S., Ziegler, J., Tetzlaff, L.: Comparison of Tag Cloud Layouts: Task-Related Performance and Visual Exploration. In: Gross, T., Gulliksen, J., Kotzé, P., Oestreicher, L., Palanque, P., Prates, R.O., Winckler, M. (eds.) INTERACT 2009. LNCS, vol. 5726, pp. 392–404. Springer, Heidelberg (2009)
Karypis, G.: CLUTO - a clustering toolkit. Technical Report #02-017 (November 2003)
Rodgers, P., Mutton, P., Flower, J.: Dynamic Euler Diagram Drawing. In: Visual Languages and Human Centric Computing (2004)
Schrammel, J., Leitner, M., Tscheligi, M.: Semantically structured tag clouds: an empirical evaluation of clustered presentation approaches. In: Proc. CHI 2009 (2009)
Schrammel, J., Deutsch, S., Tscheligi, M.: The Visual Perception of Tag Clouds - Results from an Eye Tracking Study. In: Proc. INTERACT 2009 (2009)
Steinbach, M., Karypis, G., Kumar, V.: A comparison of document clustering techniques. In: Grobelnik, M., Mladenic, D., Milic-Frayling, N. (eds.) KDD 2000 Workshop on Text Mining, Boston, MA (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 IFIP International Federation for Information Processing
About this paper
Cite this paper
Schrammel, J. (2011). Exploring New Ways of Utilizing Automated Clustering and Machine Learning Techniques in Information Visualization. In: Campos, P., Graham, N., Jorge, J., Nunes, N., Palanque, P., Winckler, M. (eds) Human-Computer Interaction – INTERACT 2011. INTERACT 2011. Lecture Notes in Computer Science, vol 6949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23768-3_41
Download citation
DOI: https://doi.org/10.1007/978-3-642-23768-3_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23767-6
Online ISBN: 978-3-642-23768-3
eBook Packages: Computer ScienceComputer Science (R0)