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Auflistung nach Autor:in "Keim, Daniel A."

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  • Konferenzbeitrag
    Analyzing electronic mail using temporal, spatial, and content-based visualization techniques
    (Informatk 2005. Informatik Live! Band 1, 2005) Keim, Daniel A.; Mansmann, Florian; Schreck, Tobias
    Email is one of the most widely-used means of communication, as evidenced by the soaring rates rates of mailing volumes since the introduction of email as an Internet service. While considerable work has been done in improving the efficiency of email management, there is a need for improving its functionality (effectiveness). Typically, users are given few means to intelligently explore the wealth of cumulated information in their email archives. We address these shortcomings by designing Information Visualization tools for email data. We have devised the MailExplorer system which aims at enabling the user to explore large quantities of email data, reflecting the rich meta data and content stored in email collections. The system allows its users to visually analyze temporal and spatial distribution properties, as well as content-based characteristics in their email archives.
  • Konferenzbeitrag
    Hierarchy-driven Visual Exploration of Multidimensional Data Cubes
    (Datenbanksysteme in Business, Technologie und Web (BTW 2007) – 12. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS), 2007) Mansmann, Svetlana; Mansmann, Florian; Scholl, Marc H.; Keim, Daniel A.
    Analysts interact with OLAP data in a predominantly “drill-down” fashion, i.e. gradually descending from a coarsely grained overview towards the desired level of detail. Analysis tools enable visual exploration as a sequence of navigation steps in the data cubes and their dimensional hierarchies. However, most state-of-the-art solutions are limited either in their capacity to handle complex multidimensional data or in the ability of their visual metaphors to provide an overview+details context. This work proposes an explorative framework for OLAP data based on a simple but powerful approach to analyzing data cubes of virtually arbitrary complexity. The data is queried using an intuitive navigation in which each dimension is represented by its hierarchy schema. Any granularity level can be dragged into the visualization to serve as an disaggregation axis. The results of the iterative exploration are mapped to a specified visualization technique. We favor hierarchical layouts for their natural ability to show step-wise decomposition of aggregate values. The power of the tool to support various application scenarios is demonstrated by presenting use cases from different domains and the visualization techniques suitable for solving specific analysis tasks.
  • Konferenzbeitrag
    Interactive analysis of NetFlows for misuse detection inlarge IP networks
    (2. DFN-Forum Kommunikationstechnologien, 2009) Mansmann, Florian; Fischer, Fabian; Keim, Daniel A.; Pietzko, Stephan; Waldvogel, Marcel
    While more and more applications require higher network bandwidth, there is also a tendency that large portions of this bandwidth are misused for dubious purposes, such as unauthorized VoIP, file sharing, or criminal botnet activity. Automatic intrusion detection methods can detect a large portion of such misuse, but novel patterns can only be detected by humans. Moreover, interpretation of large amounts of alerts imposes new challenges on the analysts. The goal of this paper is to present the visual analysis system NFlowVis to interactively detect unwanted usage of the network infrastructure either by pivoting NetFlows using IDS alerts or by specifying usage patterns, such as sets of suspicious port numbers. Thereby, our work focuses on providing a scalable approach to store and retrieve large quantities of NetFlows by means of a database management system.
  • Zeitschriftenartikel
    Visuelle Textanalyse
    (Informatik-Spektrum: Vol. 33, No. 6, 2010) Rohrdantz, Christian; Koch, Steffen; Jochim, Charles; Heyer, Gerhard; Scheuermann, Gerik; Ertl, Thomas; Schütze, Hinrich; Keim, Daniel A.
    Methoden und Techniken zur automatischen Verarbeitung und inhaltlichen Erfassung großer Mengen an Textdokumenten haben in den vergangenen Jahren enorm an Bedeutung gewonnen. Während einerseits die Verfügbarkeit und der Zugang zu digitalisierten Textdokumenten bis dato in ungeahntem Maße gestiegen sind, erweist sich die Erfassung des semantischen Inhalts solcher Dokumentsammlungen als problematisch. Dem expandierenden Forschungsfeld der visuellen Textanalyse und Textvisualisierung kommt dabei eine Schlüsselrolle bei der Lösung von Problemstellungen aus der Praxis zu. Anhand aktueller Anwendungsbeispiele und einem Überblick über den Stand der Forschung erläutert dieser Artikel die vielfältigen Möglichkeiten, die sich durch visuelle Textanalyse ergeben.