Björn Engelmann, M.Sc.

Profile

Björn Engelmann is a research associate at the Institute of Information Science at TH Köln (University of Applied Sciences). He is part of the team led by Prof. Philipp Schaer. He works in the area of information retrieval and recommender systems.

The project JoIE, which is funded by the Klaus Tschira Foundation, is a collaboration between SMC and TH Köln. As a Research associate, Björn will develop a virtual environment to support data journalism. He studied Computer Science at the Technical University of Dortmund with a focus on Data Science and philosophy. With a passion for Machine Learning, his previous studies analyzed adversarial inputs for neural networks.

List of Publications

2024

Context-Driven Interactive Query Simulations Based on Generative Large Language Models.
In: ECIR 2024. 2024.
Björn Engelmann, Timo Breuer, Jana Isabelle Friese, Philipp Schaer and Norbert Fuhr.
[pdf]  [BibTeX] 

2023

Reliable Rules for Relation Extraction in a Multimodal Setting.
In: B. König-Ries, S. Scherzinger, W. Lehner and G. Vossen, editors, Datenbanksysteme für Business, Technologie und Web (BTW 2023), 20. Fachtagung des GI-Fachbereichs ,,Datenbanken und Informationssysteme" (DBIS), 06.-10, März 2023, Dresden, Germany, Proceedings, volume P-331, series LNI, pages 1009-1021. Gesellschaft für Informatik e.V., 2023.
Björn Engelmann and Philipp Schaer.
[doi] [pdf]  [BibTeX] 
Simulating Users in Interactive Web Table Retrieval.
In: CIKM. ACM, 2023. to appear
Björn Engelmann, Timo Breuer and Philipp Schaer.
[pdf]  [BibTeX] 
Text Simplification of Scientific Texts for Non-Expert Readers.
In: SimpleText@CLEF-2023, volume abs/2307.03569, series CEUR Workshop Proceedings. 2023.
Björn Engelmann, Fabian Haak, Christin Katharina Kreutz, Narjes Nikzad-Khasmakhi and Philipp Schaer.
[doi] [pdf]  [BibTeX] 

2021

IRCologne at TREC 2021 News Track - Relation-based re-ranking for background linking.
In: TREC. National Institute of Standards and Technology (NIST), 2021.
Björn Engelmann and Philipp Schaer.
[pdf]  [BibTeX] 
IRCologne at GermEval 2021: Toxicity Classification.
In: Proceedings of the GermEval 2021 Shared Task on the Identification of Toxic, Engaging, and Fact-Claiming Comments, pages 47-53. Association for Computational Linguistics, Duesseldorf, Germany, 2021.
Fabian Haak and Björn Engelmann.
[doi] [pdf]  [abstract]  [BibTeX] 

M.Sc.Björn Engelmann

Role
Researcher / PhD Student
Mail
bjoern.engelmann@th-koeln.de
Room
B4.280