Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen


Kraker Peter, Wagner Claudia, Jeanquartier Fleur, Lindstaedt Stefanie

On the Way to a Science Intelligence: Visualizing TEL Tweets for Trend Detection

Sixth European Conference on Technology Enhanced Learning (EC-TEL 2011), Springer, 2011

This paper presents an adaptable system for detecting trends based on the micro-blogging service Twitter, and sets out to explore to what extent such a tool can support researchers. Twitter has high uptake in the scientific community, but there is a need for a means of extracting the most important topics from a Twitter stream. There are too many tweets to read them all, and there is no organized way of keeping up with the backlog. Following the cues of visual analytics, we use visualizations to show both the temporal evolution of topics, and the relations between different topics. The Twitter Trend Detection was evaluated in the domain of Technology Enhanced Learning (TEL). The evaluation results indicate that our prototype supports trend detection but reveals the need for refined preprocessing, and further zooming and filtering facilities.

Beham Günter, Jeanquartier Fleur, Lindstaedt Stefanie

iAPOSDLE - An Approach to Mobile Work-Integrated Learning

Sustaining TEL: From Innovation to Learning and Practice, Proceedings of EC-TEL 2010, Wolpers, M., Kirschner, P. A., Scheffel, M., Lindstaedt, S. N., Dimitrova, V., Springer, 2010

This paper introduces iAPOSDLE, a mobile application enabling the use of work-integrated learning services without being limited by location. iAPOSDLE makes use of the APOSDLE WIL system for self-directed work-integrated learning support, and extends its range of application to mobile learning. Core features of iAPOSDLE are described and possible extensions are discussed.

Jeanquartier Fleur, Kröll Mark, Strohmaier M.

Intent Tag Clouds: An Intentional Approach To Visual Text Analysis

Proceedings of the Workshop on Semantic Multimedia Database Technologies, 10th International Workshop of the Multimedia Metadata Community (SeMuDaTe2009), CEUR Workshop Proceedings Volume 539, 2009

Getting a quick impression of the author's intention of a text is a task often performed. An author's intention plays a major role in successfully understanding a text. For supporting readers in this task, we present an intentional approach to visual text analysis, making use of tag clouds. The objectiveof tag clouds is presenting meta-information in a visually appealing way. However there is also much uncertainty associated with tag clouds, such as giving the wrong impression. It is not clear whether the author's intent can be grasped clearly while looking at a corresponding tag cloud. Therefore it is interesting to ask to what extent, with tag clouds, it is possible to support the user in understanding intentions expressed. In order to answer this question, we construct an intentional perspective on textual content. Based on an existing algorithm for extracting intent annotations from textual content we present a prototypical implementation to produce intent tag clouds, and describe a formative testing, illustrating how intent visualizations may support readers in understanding a text successfully. With the initial prototype, we conducted user studies of our intentional tag cloud visualization and a comparison with a traditional one that visualizes frequent terms. The evaluation's results indicate, that intent tag clouds have a positive effect on supporting users in grasping an author's intent.

Ley Tobias, Jeanquartier Fleur, Anna Maria Köck

Neurovation - Kreativitätstool für Knowledge Worker

In R. Willfort, K. Tochtermann, A. Neubauer (Hrsg.): Creativity@Work für Wissensarbeit, Shaker Verlag, Aachen, 2007

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