Text Mining Archives - Human-Computer Interaction & Visual Analyitics Reasearch Group (vis) at Darmstadt University of Applied Sciences (h

Paper accepted at 14th International Symposium on Visual Computing (ISVC 2019)

26/08/2019/in Allgemein, Event, Publication, Research, Scitics /by Dirk Burkhardt

Our paper entitled “A Visual Analytics Approach for Analyzing Technological Trends in Technology and Innovation Management” is accepted at the visual computing conference ISVC 2019 in Lake Tahoe, NV, USA. The purpose of the International Symposium on Visual Computing (ISVC) is to provide a first-class 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

Abstract:
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

More information about the technology: Scitics for Visual Trend Analytics

Best Paper Award at the iV 2019

10/07/2019/in Publication, Scitics /by Dirk Burkhardt

We are proud to announce that our last paper “Visual Analytics for Analyzing Technological Trends from Text” at the iV2019 conference in Paris was honored with “The Best Paper Award” for the innovative contribution in terms of originality of concepts and application. The “Best Paper Awards” is given to contributions which will be selected by the committee among the papers presented in iV2019 and applied for the award. Study’s relevance to the symposium’s scope, its scientific contribution, writing/presentation style will be considered in the evaluation process as well.

A short interview can be found here (German).

The Information Visualisation Conference (iV) is an international conference that aims to provide a foundation for integrating the human-centered, technological and strategic aspects of information visualization to promote international exchange, cooperation and development.

Paper accepted at 23rd Internation Conference Information Visualization (iV 2019)

10/05/2019/in Allgemein, Event, Publication, Research, Scitics /by Dirk Burkhardt

We are very glad to be accepted for presenting our paper titled “Visual Analytics for Analyzing Technological Trends from Text” at the high-class conference iV 2019 in Paris, France. The Information Visualisation Conference (iV) is an international conference that aims to provide a foundation for integrating the human-centered, technological and strategic aspects of information visualization to promote international exchange, cooperation and development.

Paper: Visual Analytics for Analyzing Technological Trends from Text

Abstract:
The awareness of emerging technologies is essential for strategic decision making in enterprises. Emerging and decreasing technological trends could lead to strengthening the competitiveness and market positioning. The exploration, detection and identification of such trends can be essentially supported through information visualization, trend mining and in particular through the combination of those. Commonly, trends appear first in science and scientific documents. However, those documents do not provide sufficient information for analyzing and identifying emerging trends. It is necessary to enrich data, extract information from the integrated data, measure the gradient of trends over time and provide effective interactive visualizations. We introduce in this paper an approach for integrating, enriching, mining, analyzing, identifying and visualizing emerging trends from scientific documents. Our approach enhances the state of the art in visual trend analytics by investigating the entire analysis process and providing an approach for enabling human to explore undetected potentially emerging trends.

Link to paper/fulltext: https://dx.doi.org/10.1109/IV.2019.00041

More information about the technology: Scitics for Visual Trend Analytics

Demo video:

24rd International Conference Information Visualization (iV 2020)

27/11/2019/in Conference /by Dirk Burkhardt

We are co-organizing track International Symposium Visual Analytics and Data Science at the next International Information Visualisation Conference (iV 2020) in Vienna, Austria. The Information Visualisation Conference (iV) is an international conference that aims to provide a foundation for integrating the human-centered, technological and strategic aspects of information visualization to promote international exchange, cooperation and development. The scope of the conference covers the following topics:

Combining visual and computational methods of Data Analysis, Machine Learning and Artificial Intelligence
Visual Analytics models and approaches
Novel Visual Analytics applications
Visual Trend Analytics
Visual Analytics of spatial, temporal, and spatio-temporal data
Knowledge construction and management in Visual Analytics
Guidance in Visual Analytics
Intelligent approaches of Visual Analytics and Data Science
Adaptive Visual Analytics
Cognitive approaches and explanations for Visual Analytics
Visual Analytics for explaining AI
Visualization of Data Mining algorithms
Empirical performance studies
Evaluation of Visual Data Mining methods
Collaborative Visual

Please note the iV2020 Call for Papers (CfP).

The Visual Analytics and Data Science track is organized via the 12th International Symposium Visual Analytics and Data Science. Visual Analytics is viewed as the science of analytical reasoning empowered by interactive visualizations. It combines interactive visualizations with models and approaches of machine learning and artificial intelligence, enabling solving complex analytical tasks by uncovering hidden patterns in data. The research on Visual Analytics is closely related to that of Data Science. Both areas seek to enhance the knowledge discovery process using machine learning, data mining and artificial intelligence methods, whereas Visual Analytics allows commonly a direct manipulation of the underlying models through graphical representations. By leveraging human perception of the visual space, patterns that might not otherwise be discovered. Visual Analytics utilizes concepts from a wide variety of disciplines, including Computer Graphics, Information Visualization, Machine Learning, Artificial Intelligence, Knowledge Discovery, Cognition and Visual Perception. The scope of the VA track covers the following topics:

Combining visual and computational methods of Data Analysis, Machine Learning and Artificial Intelligence
Visual Analytics models and approaches
Novel Visual Analytics applications
Visual Trend Analytics
Visual Analytics of spatial, temporal, and spatio-temporal data
Knowledge construction and management in Visual Analytics
Guidance in Visual Analytics
Intelligent approaches of Visual Analytics and Data Science
Adaptive Visual Analytics
Cognitive approaches and explanations for Visual Analytics
Visual Analytics for explaining AI
Visualization of Data Mining algorithms
Empirical performance studies
Evaluation of Visual Data Mining methods
Collaborative Visual Analytics and Data Science
Computational steering for long-running Data Mining applications
Reviews and surveys of related literature

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