Exploring New Ways of Utilizing Automated Clustering and Machine Learning Techniques in Information Visualization - Human-Computer Interaction – INTERACT 2011 Access content directly
Conference Papers Year : 2011

Exploring New Ways of Utilizing Automated Clustering and Machine Learning Techniques in Information Visualization

Johann Schrammel
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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.
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hal-01596998 , version 1 (28-09-2017)

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Johann Schrammel. Exploring New Ways of Utilizing Automated Clustering and Machine Learning Techniques in Information Visualization. 13th International Conference on Human-Computer Interaction (INTERACT), Sep 2011, Lisbon, Portugal. pp.394-397, ⟨10.1007/978-3-642-23768-3_41⟩. ⟨hal-01596998⟩
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