Conference paper Open Access

A Mobile Visual Analytics Approach for Instant Trend Analysis in Mobile Contexts

Dirk Burkhardt; Kawa Nazemi; Arjan Kuijper; Egils Ginters

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.

Files (2.1 MB)
Name Size
VARE2019_MobileTrendAnalytics.pdf
md5:5287159005d85b9f9c3898e0d337bfe1
2.1 MB Download
  • Allan, J., Papka, R., Lavrenko, V., 1998. On-line new event detection and tracking. In Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, pp. 37-45. ACM.

  • Booth, P., 2014. An Introduction to Human-Computer Interaction. Psychology Press.

  • Burkhardt, D., Breyer, M., Nazemi, K., Kuijper, A., 2011. Search Intention Analysis for User-Centered Adaptive Visualizations. Universal Access in Human-Computer Interaction. Design for All and eInclusion. UAHCI 2011. Lecture Notes in Computer Science, 6765. Berlin, Germany: Springer.

  • Burkhardt, D., Pattan, S., Nazemi, K., Kuijper, A., 2016. Search Intention Analysis for Task- and User-Centered Visualization in Big Data Applications. Procedia Computer Science, 104, pp. 539-547. Elsevier.

  • Card, S. K., Mackinlay, J. D., Shneiderman, B., 1999. Readings in Information Visualization: Using Vision to Think. 1st ed. Morgan Kaufmann.

  • Chandler, R. E., Scott, M., 2011. Statistical methods for trend detection and analysis in the environmental sciences, John Wiley & Sons.

  • Ginters, E., Aizstrauts, A., Dreija, G. et al., 2014. Skopje Bicycle Inter-modality Simulator – einvolvement through simulation and ticketing. In Proceedings of 26th European Modelling & Simulation Symposium (EMSS 2014), pp. 557- 563. Bordeaux, France.

  • Gray, K. L., 2007. Comparison of Trend Detection Methods. PhD thesis, Department of Mathematics, University of Montana.

  • Havre, S., Hetzler, E., Whitney, P. Nowell, L., 2002. Themeriver: Visualizing thematic changes in large document collections. IEEE transactions on visualization and computer graphics, 8(1), pp. 9– 20. IEEE.

  • Hwang, M, Inm M, Ha, S., Lee, K., 2017. Tasis: Trend analysis system for international standards. In 2017 ITU Kaleidoscope: Challenges for a Data- Driven Society (ITU K), pp. 1-8, IEEE.

  • Kim, Y., Tian, Y., Jeong, Y., Jihee, R., Myaeng, S.-H., 2009. Automatic discovery of technology trends from patent text. In Proceedings of the 2009 ACM symposium on Applied Computing, pp. 1480- 1487. ACM.

  • Kontostathis, A., Galitsky, L. M., Pottenger, W. M., Roy, S., Phelps, D. J., 2004. A survey of emerging trend detection in textual data mining. In Survey of Text Mining, pp. 185-224. Springer.

  • Lent, B., Agrawal, R., Srikant, R., 1997. Discovering trends in text databases. In KDD, volume 97, pp. 227–230.

  • Liu, S., Zhou, M. X., Pan, S., Quian, W., Cai, W., Lian, X., 2009. Interactive, topic-based visual text summarization and analysis. In Proceedings of the 18th ACM conference on Information and knowledge management, pp. 543–552. ACM.

  • Nazemi, K., Burkhardt, D., 2019. Visual analytical dashboards for comparative analytical tasks – a case study on mobility and transportation. Procedia Computer Science, 149, pp. 138-150. Elsevier.

  • Nazemi, K., Burkhardt, D., 2019. Visual Analytics for Analyzing Technological Trends from Text. In Proceedings of 23rd International Conference Information Visualisation (IV), pp. 191-200. IEEE.

  • Nazemi, K., Burkhardt, D., Breyer, M., Stab, C., Fellner, D. W., 2010. Semantic Visualization Cockpit: Adaptable Composition of Semantics- Visualization Techniques for Knowledge- Exploration. Proceedings of Interactive Computer Aided Learning (ICL 2010), pp. 163–173. Kassel, Germany: Kassel University Press.

  • Nazemi, K., Burkhardt, D., Ginters, E., Kohlhammer, J., 2015. Semantics Visualization - Definition, Approaches and Challenges. Procedia Computer Science, 75, pp. 75-83. Elsevier.

  • Nazemi, K., Burkhardt, D., Hoppe, D., Nazemi, M., Kohlhammer, J., 2015. Web-based Evaluation of Information Visualization. In Procedia Manufacturing, Vol. 3, pp. 5527-5534. Elsevier.

  • Nazemi, K., Retz, R., Burkhardt, D., Kuijper, A., Kohlhammer, J., Fellner, D. W., 2015. Visual trend analysis with digital libraries. Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business (i-KNOW '15). New York, USA: ACM.

  • Pottenger, W. M., Yang, T.-h., 2001. Detecting emerging concepts in textual data mining. Computational information retrieval, 100.

  • Roudaut, A., 2009. Visualization and interaction techniques for mobile devices. In CHI'09 Extended Abstracts on Human Factors in Computing Systems, pp. 3153-3156. ACM.

  • Sharma, S., Swayne, S. A., Obimbo, C., 2016. Trend analysis and change point techniques: a survey. Energy, Ecology and Environment, 1(3), 123-130.

  • Shneiderman, B., 1996. The eyes have it: a task by data type taxonomy for information visualizations. Proceedings 1996 IEEE Symposium on Visual Languages, pp. 336-343. Boulder, USA.

  • Think Design, 2018. Trend Analysis. Available from: https://think.design/user-design-research/trendanalysis/ [accessed 14/04/2019].

  • Wang, Y., Zhou, L.-Z., Feng, J.-H., Xie, L., Yuan, C., 2006. 2D/3D Web Visualization on Mobile Devices. Web Information Systems–WISE 2006, pp. 536-547.

22
18
views
downloads
All versions This version
Views 2222
Downloads 1818
Data volume 38.2 MB38.2 MB
Unique views 1414
Unique downloads 1212

Share

Cite as