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Auflistung nach Autor:in "Schumacher, Kinga"

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  • Konferenzbeitrag
    A paper-based technology for personal knowledge management
    (WM2009: 5th conference on professional knowledge management, 2009) Schumacher, Kinga; Liwicki, Marcus; Dengel, Andreas
    In this paper we extend the Semantic Desktop with a novel input modality: handwriting on paper. This extension allows for annotating printed documents with handwritten notes, which are then recognized, interpreted and integrated into the personal knowledge space. Thus it supports personal knowledge work on paper. In particular, the user can mark any text segment and annotate it with his or her own comments. The semantic of these comments and marks are then interpreted and, finally, the result is included in the user's Semantic Desktop. The methodology for finding the intended meaning of the annotation in context of the marked text is presented in this paper. To demonstrate the applicability of our approach, we have implemented a prototype for the NEPOMUK Semantic Desktop.
  • Zeitschriftenartikel
    Semantic Desktop for the End-UserSemantic Desktop für Anwender
    (i-com: Vol. 8, No. 3, 2009) Grimnes, Gunnar Aastrand; Adrian, Benjamin; Schwarz, Sven; Maus, Heiko; Schumacher, Kinga; Sauermann, Leo
    This article describes the Semantic Desktop. We give insights into the core services that aim to improve personal knowledge management on the desktop. We describe these core components of our Semantic Desktop system and give evaluation results. Results of a long-term study reveal effects of using the Semantic Desktop on personal knowledge work.
  • Zeitschriftenartikel
    The AI Methods, Capabilities and Criticality Grid
    (KI - Künstliche Intelligenz: Vol. 35, No. 0, 2021) Schmid, Thomas; Hildesheim, Wolfgang; Holoyad, Taras; Schumacher, Kinga
    Many artificial intelligence (AI) technologies developed over the past decades have reached market maturity and are now being commercially distributed in digital products and services. Therefore, national and international AI standards are currently being developed in order to achieve technical interoperability as well as reliability and transparency. To this end, we propose to classify AI applications in terms of the algorithmic methods used, the capabilities to be achieved and the level of criticality. The resulting three-dimensional classification scheme, termed the AI Methods, Capabilities and Criticality (AI- $$\hbox {MC}^2$$ MC 2 ) Grid, combines current recommendations of the EU Commission with an ethical dimension proposed by the Data Ethics Commission of the German Federal Government (Datenethikkommission der Bundesregierung: Gutachten. Berlin, 2019). As a whole, the AI- $$\hbox {MC}^2$$ MC 2 Grid allows not only to gain an overview of the implications of a given AI application as well as to compare efficiently different AI applications within a given market or implemented by different AI technologies. It is designed as a core tool to define and manage norms, standards and compliance of AI applications, but helps to manage AI solutions in general as well.
  • Konferenzbeitrag
    Troubleshooting Conversations: Exploring Chatbot Repair Strategies
    (Proceedings of Mensch und Computer 2024, 2024) Wilhelm, Marilena; Schwaetzer, Eva; Otten, Tabea; Zobel, Theresa Elfriede Isa; Schumacher, Kinga
    Chatbots are increasingly used in various domains, but since misunderstandings nonetheless occur, robust strategies are required to handle these misunderstandings and ensure smooth interactions. The evaluation of a faulty chatbot can depend on various factors, for example the task domain or the characteristics of the user. This short paper provides an overview of three different repair strategies for chatbots, taking into account the users’ affinity for technology. The conducted experimental psychological study investigates these three strategies, i.e. the requests for rephrasing, offering suggestions of what might be meant, and politeness to handle conversational errors. Results indicate that providing suggestions has a positive influence on the perceived Accuracy and Likability of the chatbot. Additionally, it seems that the combination of repair strategies should also be considered. Overall, this research contributes to a deeper understanding of ways to recover from a misunderstanding and provides guidelines for the implementation of different repair strategies for chatbot interaction.