Computational Linguistics
Department at Trier University
The Chair of Computational Linguistics at Trier University has been held since 2019 by Prof Dr Achim Rettinger, who heads the Computational Linguistics team. Computational Linguistics at Trier University focuses on the machine learning of knowledge representation, primarily from textual media. These are used to understand natural language, to analyse media and to integrate and provide knowledge.
The page is currently in development.
The following content is preliminary and will change.
Projects
TWin of Online Social Networks
- Funding
- Horizon Europe Research and Innovation Actions
- Duration
- Apr 2023 – Mar 2026
- Contact
- Univ.-Prof. Dr. Achim Rettinger
It is a widely shared concern by experts that Online Social Networks (OSNs) have transformed public debate in harmful ways. Personalization algorithms can create filter bubbles and echo chambers which reinforces and polarizes the users’ opinions. Thus, OSNs have been blamed for spreading false information. To this point, tech-companies argue that there is no unequivocal empirical evidence and that they should not interfere with user behavior. The TWON project aims to provide scientific evidence on both counterarguments, whether social networks have undesirable effects on democratic debates and how they inferfere with user behavior. This will be done by creating digital twins of online social networks to estimate the effects of a change in the system.
Team
Univ.-Prof. Dr. Achim Rettinger
Chair of Computational Linguistics
Achim Rettinger is a full professor at Trier University, a director at FZI Forschungszentrum Informatik and supervising director at HoP House of Participation. He leads the krAil research group. Prof. Rettinger’s research spans machine learning, natural language understanding, knowledge representation, and the Web of Data. His group’s work has received multiple best paper, demo, challenge, and presentation awards. He has served as a senior Program Committee member of the International Semantic Web Conference (ISWC) and as a track chair and steering committee member of the European Semantic Web Conference (ESWC). He is also a member of the Board of Directors of the AI for Good Foundation.
Publications
Learning from recorded games: A scoring policy for simulated soccer agents
Univ.-Prof. Dr. Achim Rettinger
Fachberichte Informatik, 2005
Abstract
This paper outlines the implementation of a new scoring policy for the agents of the Simulated Robot Soccer team from the University of Koblenz, called RoboLog. The applied technique is capable of acting in real time in the dynamic environment of the RoboCup Simulation League and uses data obtained from prerecorded soccer games for supervised neural network learning. The benchmark used for testing this approach is the Optimal Scoring Problem stated as finding the point in the goal where the probability of scoring is the highest when the ball is shot to this point in a given situation. Goalshot situations from numerous logfiles are extracted and employed for the training of two independent multi layered perceptrons. Beside the usage as training patterns the gained data is evaluated statistically and provides interesting general insights into goalshots carried out lately in Simulated Robot Soccer.