2019 |
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2. | ![]() | Burkhardt, Dirk; Nazemi, Kawa; Kuijper, Arjan; Ginters, Egils A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts Proceedings Article In: 5th International Conference of the Virtual and Augmented Reality in Education (VARE2019), pp. 11–19, CAL-TEK SRL, Rende, Italy, 2019, ISBN: 978-88-85741-41-6, (Nominated for Best Paper Award). Abstract | Links | BibTeX | Tags: Business Analytics, Decision Support Systems, Human-Computer Interaction, Information Visualization, Mobile Devices, Mobile Visual Analytics, Visual Trend Analysis @inproceedings{Burkhardt2019b, The awareness of market trends becomes relevant for a broad number of market branches, in particular the more they are challenged by the digitalization. Trend analysis solutions help business executives identifying upcoming trends early. But solid market analysis takes their time and are often not available on consulting or strategy discussions. This circumstance often leads to unproductive debates where no clear strategy, technology etc. could be identified. Therefore, we propose a mobile visual trend analysis approach that enables a quick trend analysis to identify at least the most relevant and irrelevant aspects to focus debates on the relevant options. To enable an analysis like this, the exhausting analysis on powerful workstations with large screens has to adopted to mobile devices within a mobile behavior. Our main contribution is the therefore a new approach of a mobile knowledge cockpit, which provides different analytical visualizations within and intuitive interaction design. |
1. | Nazemi, Kawa; Burkhardt, Dirk Visual Text Analytics for Technology and Innovation Management Miscellaneous Presented at OpenRheinMain Conference (ORM2019), 13 September 2019, Darmstadt, Germany, 2019. Abstract | Links | BibTeX | Tags: Business Analytics, Innovation Management, Technology Management, Text Analysis, Trend Analytics, Visual Text Analytics @misc{Nazemi2019b, Through coupling of Data Mining, Visual Analytics and Business Analytics techniques, we created a novel solution for strategic market analysis with focus on early trend recognition. As fundament, we are able to consider a variety of text data, as for instance research publications available from a number of (open access) digital libraries, reports and other data from companies, web data about markets as well as news from companies or social media data etc. In an advanced and unified processing pipeline, the information is extracted and mined for a variety of analytical purposes. Via an interactive analysis user-interface, domain experts are able to analysis strong and weak signals in perspective of upcoming trends. |
2019 |
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2. | ![]() | A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts Proceedings Article In: 5th International Conference of the Virtual and Augmented Reality in Education (VARE2019), pp. 11–19, CAL-TEK SRL, Rende, Italy, 2019, ISBN: 978-88-85741-41-6, (Nominated for Best Paper Award). |
1. | Visual Text Analytics for Technology and Innovation Management Miscellaneous Presented at OpenRheinMain Conference (ORM2019), 13 September 2019, Darmstadt, Germany, 2019. |