Abstract
Visual Analytics provides with a combination of automated techniques and interactive visualizations huge analysis possibilities in technology and innovation management. Thereby not only the use of machine learning data mining methods plays an important role. Due to the high interaction capabilities, it provides a more user-centered approach, where users are able to manipulate the entire analysis process and get the most valuable information. Existing Visual Analytics systems for Trend Analytics and technology and innovation management do not really make use of this unique feature and almost neglect the human in the analysis process. Outcomes from research in information search, information visualization and technology management can lead to more sophisticated Visual Analytics systems that involved the human in the entire analysis process. We propose in this paper a new interaction approach for Visual Analytics in technology and innovation management with a special focus on technological trend analytics.
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Acknowledgments
This work was partially funded by the Hessen State Ministry for Higher Education, Research and the Arts within the program “Forschung für die Praxis” and was conducted within the research group on Human-Computer Interaction and Visual Analytics (https://vis.h-da.de). The presentation of this work was supported by the Research Center for Digital Communication & Media Innovation of the Darmstadt University of Applied Sciences.
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Nazemi, K., Burkhardt, D. (2019). A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2019. Lecture Notes in Computer Science(), vol 11845. Springer, Cham. https://doi.org/10.1007/978-3-030-33723-0_23
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DOI: https://doi.org/10.1007/978-3-030-33723-0_23
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