Programm Fachgruppe Wissensmanagement 

Day 1

13:00 – 13:30 Uhr
Prof. Dr. Stefan Wrobel (Institute Director Fraunhofer IAIS)

13:30 – 15:00 Uhr
Prof. Dr. Geoff Webb (Monash University)

Time series classification at scale

Time series classification is a fundamental data science problem, providing understanding of dynamic processes as they evolve over time. The recent introduction of ensemble techniques has revolutionised this field, greatly increasing accuracy, but at a cost of increasing already burdensome computational overheads.  I present new time series classification technologies that achieve the same accuracy as recent state-of-the-art developments, but with many orders of magnitude greater efficiency and scalability.  These make time series classification feasible at hitherto unattainable scale.

15:00 – 15:30 Uhr

15:30 – 16:30 Uhr
Joint Research Track

Solving Abstract Reasoning Tasks with Grammatical Evolution
(Raphael Fischer, Matthias Jakobs, Sascha Mücke and Katharina Morik)

Construction of a Corpus for the Evaluation of Textual Case-based Reasoning Architectures
(Andreas Korger and Joachim Baumeister)

Modeling Interdependent Preferences over Incomplete Knowledge Graph Query Answers
(Till Affeldt, Stephan Mennicke and Wolf-Tilo Balke)

16:30 – 18:00 Uhr
Poster Session

Day 2

13:00 – 14:30 Uhr
Prof. Dr. Kristian Kersting (TU Darmstadt)

On Hybrid and Systems AI
Our minds make inferences that appear to go far beyond standard machine learning. Whereas people can learn richer representations and use them for a wider range of learning tasks, machine learning algorithms have been mainly employed in a stand-alone context, constructing a single function from a table of training examples. In this talk, I shall touch upon a view on AI and machine learning, called Systems AI, that can help capturing these human learning aspects by combining different AI and ML models using high-level programming. Since inference remains intractable, existing approaches leverage deep learning for inference. Instead of “just going down the neural road,” I shall argue to also use probabilistic circuits, a deep but tractable architecture for probability distributions. This hybrid approach can speed up inference  as I shall illustrate for unsupervised science understanding, database queries and automating density estimation.

14:30 – 15:30 Uhr

  • Visualizing the behaviour of CBR agents in a FPS scenario Visualizing the behaviour of CBR agents in a FPS scenario
    (Jobst-Julius Bartels, Sebastian Viefhaus, Philipp Yasrebi-Soppa, Pascal Reuss and Klaus-Dieter Althoff)
  • Development and Implementation of a Case-Based Reasoning Approach to Speed-Up Deep Reinforcement Learning through Case-Injection for AI Gameplay
    (Marcel Heinz, Jakob Michael Schoenborn and Klaus-Dieter Althoff)
  • Towards case-based reasoning in real-time strategy environments with SEASALT
    (Jakob Michael Schoenborn and Klaus-Dieter Althoff)

15:30 – 16:00 Uhr

16:00 – 17:00

  • Process Mining for Case Acquisition in Oncology: A Systematic Literature Review Process Mining for Case Acquisition in Oncology: A Systematic Literature Review
    (Joscha Grüger, Ralph Bergmann, Yavuz Kazik and Martin Kuhn)
  • Student Graduation Projects in the Context of Framework for AI-Based Support of Early Conceptual Phases in Architecture
    (Viktor Eisenstadt, Klaus-Dieter Althoff and Christoph Langenhan)

17:00 – 18:00 Uhr
Community Meeting

Day 3

14:00 – 15:00

  • Understanding the consequences of adopting the Internet of Things in small- and medium-sized enterprises
    (Hannes Reil, Marlen Rimbeck, Michael Leyer and Jutta Stumpf-Wollersheim)
  • A Concept for the Automated Reconfiguration of Quadcopters
    (Kaja Balzereit, Marta Fullen and Oliver Niggemann)
  • INWEND: Using CBR to automate legal assessment in the context of the EU General Data Protection Regulation
    (Clarissa Dietrich, Sebastian Schriml, Ralph Bergmann and Benjamin Raue)

15:00 – 15:30 Uhr

15:30 – 16:30 Uhr
Prof. Dr. Thomas Gärtner (TU Wien)

Interactive Machine Learning with Structured Data

In this talk I’ll give an overview of our contributions to what I call interactive machine learning. Often, interaction in Computer Science is interpreted as the interaction of humans with the computer but I intend a broader meaning of the interaction of machine learning algorithms with the real world, including but not restricted to humans. Interactions with humans span a broad range where they can be intentional and guided by the human or they can be guided by the computer such that the human is oblivious of the fact that he is being guided. Another example of an interaction with the real world is the use of machine learning algorithms in cyclic discovery processes such as drug design. Important properties of interactive machine learning algorithms include efficiency, effectiveness, responsiveness, and robustness. In the talk I will show how these can be achieved in a variety of interactive contexts.

16:30 – 17:00 Uhr

Paper Submission: June 21, 2020

The annual workshop “Fachgruppe Wissensmanagement (SIG Knowledge Management)” is organized by the Special Interest Group on Knowledge Management of the German Informatics society (GI), which aims at enabling and promoting the exchange of innovative ideas and practical applications in the field of knowledge and experience management.

The workshop will be held on September 09-11, 2020, online only.

All submissions of current research from this and adjacent areas are welcome, in particular, work in progress contributions. The latter can serve as a basis for interesting discussions among the participants and provide young researchers with feedback. We also invite researchers to contribute to the workshop by resubmitting conference papers to share their ideas with the research community. Resubmissions will not be part of the conference proceedings.

Topics of interest

Submissions from all areas contributing to the development and application of intelligent knowledge and experience management systems are welcome. We explicitly encourage paper submissions that are not mainstream but from communities within mathematics, social sciences or economics in order to obtain a more interdisciplinary view on the subject.

Topics of interest include but are not limited to:

  • New frontiers in Knowledge Management and Experience Knowledge
  • Reasoning approaches, for example case-based reasoning, probabilistic reasoning, logic-based approaches and text-based reasoning
  • Knowledge representation, for example cases, semantic networks, ontologies, context, and logics
  • Knowledge engineering, for example acquisition methods, quality assessment, versioning, maintenance, and visualization
  • Applications of Knowledge Management, for example semantic web applications, linked data, smart companion technologies, diagnosis, configuration, agent-based applications
  • User experience management and usability knowledge
  • Design and evaluation of knowledge systems
  • Practical experiences (“lessons learned”) with IT-aided KM approaches
  • Integration of Knowledge Management and business processes
  • Combination of Knowledge Management with other systems and concepts (e.g. decision support, cloud computing, Big Data)

Official workshop languages are German and English. In particular, contributions can be in English or German but presentations should be in English to ensure that English speaking participants can always follow.

Important dates

  • Submission of papers: June 21, 2020
  • Notification of acceptance: July 28, 2020
  • Camera-ready copy: August 17, 2020
  • Workshop FGWM@LWDA: September 9 – 11, 2020

Intended audience

The target group includes researchers and practitioners who are interested in developing, applying and analyzing knowledge and experience management systems as well as applicable scenarios. The workshop is also a great and affordable platform for young researchers to present their work to a larger group of researchers and get valuable feedback.

Submission guidelines

Submissions should be alternatively:

  • up to 6 pages long for short papers,
  • from 6 up to 12 pages long for full papers or PhD proposals,
  • One-pager summaries for resubmissions recently published at other renowned conferences and are not part of the LWDA proceedings.

All contributions must be submitted via EasyChair as PDF at:
Please select the track “FG-WM” when submitting your paper. The publication of the conference proceedings will be with CEUR Workshop Proceedings (CEUR-WS.org).

All papers should be formatted with Springer LNCS: http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0.

All workshop participants have to register for the LWDA 2020 conference.

Workshop chair

  • Lisa Grumbach, University of Trier
  • Pascal Reuss, University of Hildesheim

Program committee

  • Klaus-Dieter Althoff
  • Kerstin Bach
  • Joachim Baumeister
  • Ralph Bergmann
  • Lisa Grumbach
  • Andrea Kohlhase
  • Michael Kohlhase
  • Michael Leyer
  • Mirjam Minor
  • Ulrich Reimer
  • Pascal Reuss
  • Bodo Rieger
  • Christian Severin Sauer


The contact person for all questions regarding the organization of the workshop is Lisa Grumbach.


Dr. Daniel Trabold

Dr. Daniel Trabold

Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS

Schloss Birlinghoven
53757 Sankt Augustin, Germany

Phone +49 2241 14-2751

Bonn Image: ©travelview – stock.adobe.com