Paper accepted at 14th International Symposium on Visual Computing (ISVC 2019)
I’m proud to announce that our paper titled “A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management” is accepted at the high-class visual computing conference ISVC 2019 in Lake Tahoe, NV, USA. The purpose of the International Symposium on Visual Computing (ISVC) is to provide a common forum for researchers, scientists, engineers and practitioners throughout the world to present their latest research findings, ideas, developments and applications in visual computing. ISVC seeks papers describing contributions to the state of the art and state of the practice in the four central areas of visual computing: computer vision, computer graphics, virtual reality, and visualization. The paper reflects some new on-going advancements of our innovative Trend Analytics solution Scitics.
Paper: A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management
Visual Analytics provides with a combination of automated techniques and interactive visualizations huge analytics 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 do not include the human in the analysis process. Outcomes from research on 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.
Link to paper/fulltext: https://dx.doi.org/10.1007/978-3-030-33723-0_23
Link to poster: https://dx.doi.org/10.5281/zenodo.3473065
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