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Auflistung nach Autor:in "Koch, Christian"

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  • Textdokument
    A Reference Architecture for On-Premises Chatbots in Banks and Public Institutions
    (INFORMATIK 2021, 2021) Koch, Christian; Linnik, Benjamin; Pelzel, Frank; Sultanow,Eldar; Welter, Sebastian; Cox, Sean
    Chatbots have the potential to significantly increase the efficiency of banks and public institutions. Both sectors, however, are subject to special regulations and restrictions in areas such as information security and data protection. The policies of these organizations therefore, in some cases, reject the use of cloud and proprietary products because in their view they lack transparency. As a result, the implementation of chatbots in banks and public institutions often focuses on open-source and on-premises solutions; however, there are hardly any scientific guidelines on how to implement these systems. Our paper aims to close this research gap. The article proposes a reference architecture for chatbots in banks and public institutions that are a.) based on open-source software and b.) are hosted on-premises. The framework is validated by case studies at TeamBank AG and the German Federal Employment Agency. Even if our architecture is designed for these specific industries, it may also add value in other sectors – as chatbots are expected to become increasingly important for the practical application of artificial intelligence in enterprises.
  • Konferenzbeitrag
    Visualization and Machine Learning for Data Center Management
    (INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft (Workshop-Beiträge), 2019) Chircu, Alina; Sultanow, Eldar; Baum, David; Koch, Christian; Seßler, Matthias
    In this paper, we present a novel tool for data center management that incorporates data visualization and machine learning capabilities. We developed the tool in the context of an action design research project conducted at a large government agency in Germany, which hosts three highly available data centers containing more than 10,000 servers. We derived the requirements for the tool from qualitative interviews with agency employees who are familiar with monitoring the data center infrastructure as well as from a review of existing data center and other large infrastructure monitoring solutions. We implemented a web-based 3D prototype for the tool as an Angular 6 application running on Node.js, and evaluated it with the same employees. Most participants preferred the new tool, which provided a significantly better option and enabled visualization of historical data for all server instances at the same time, as well as real-time charts. Planned improvements will take advantage of the full potential of machine learning for time series forecasting.
  • Conference demo
    Web-based prototype of a visual and interactive deep learning simulation
    (Proceedings of DELFI 2024, 2024) Koch, Christian; Salmen, Frederic; Schroeder, Ulrik
    Due to its rapid development and growing relevance in society, the research field of artificial intelligence (AI) is finding its way into more and more schools. One subsection of artificial intelligence, deep learning, is especially relevant since most of the rapid development of the study field in recent years can be attributed to it. Because of its complex nature, deep learning is very suitable to be taught in a visual and interactive way, which can benefit learning outcomes. Existing solutions can convey basic knowledge about deep learning, but none of them are well suited to customization or facilitating deep understanding. We introduce a visual and interactive deep learning simulation with rich possibilities for personalization by teachers and students, usable in any web context.