1 code implementation • EMNLP 2021 • Leon Weber, Jannes Münchmeyer, Samuele Garda, Ulf Leser
Deriving and modifying graphs from natural language text has become a versatile basis technology for information extraction with applications in many subfields, such as semantic parsing or knowledge graph construction.
no code implementations • NAACL (BioNLP) 2021 • Mario Sänger, Leon Weber, Ulf Leser
This paper describes our contribution for the MEDIQA-2021 Task 1 question summarization competition.
1 code implementation • EMNLP (Louhi) 2020 • Xing David Wang, Leon Weber, Ulf Leser
Biomedical event extraction from natural text is a challenging task as it searches for complex and often nested structures describing specific relationships between multiple molecular entities, such as genes, proteins, or cellular components.
1 code implementation • BioNLP (ACL) 2022 • Xing David Wang, Ulf Leser, Leon Weber
Automatic extraction of event structures from text is a promising way to extract important facts from the evergrowing amount of biomedical literature.
1 code implementation • Bioinformatics 2024 • Arik Ermshaus, Michael Piechotta, Gina Rüter, Ulrich Keilholz, Ulf Leser, Manuela Benary
Summary preon is a fast and accurate library for the normalization of drug names and cancer types in large-scale data integration.
no code implementations • 19 Feb 2024 • Mario Sänger, Samuele Garda, Xing David Wang, Leon Weber-Genzel, Pia Droop, Benedikt Fuchs, Alan Akbik, Ulf Leser
Instead, they are applied in the wild, i. e., on application-dependent text collections different from those used for the tools' training, varying, e. g., in focus, genre, style, and text type.
no code implementations • 10 Jan 2024 • Samuele Garda, Ulf Leser
Biomedical entity linking (BEL) is the task of grounding entity mentions to a knowledge base (KB).
no code implementations • 3 Nov 2023 • Mario Sänger, Ninon De Mecquenem, Katarzyna Ewa Lewińska, Vasilis Bountris, Fabian Lehmann, Ulf Leser, Thomas Kosch
Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability, and scalability of analyses by automatic parallelization on large compute clusters.
1 code implementation • 31 Oct 2023 • Arik Ermshaus, Patrick Schäfer, Ulf Leser
Ubiquitous sensors today emit high frequency streams of numerical measurements that reflect properties of human, animal, industrial, commercial, and natural processes.
1 code implementation • Advanced Analytics and Learning on Temporal Data 2023 • Arik Ermshaus, Patrick Schäfer, Anthony Bagnall, Thomas Guyet, Georgiana Ifrim, Vincent Lemaire, Ulf Leser, Colin Leverger, Simon Malinowski
Despite its importance, existing methods demonstrate limited efficacy on real-world multivariate time series data.
1 code implementation • 22 Aug 2023 • Samuele Garda, Leon Weber-Genzel, Robert Martin, Ulf Leser
Biomedical entity linking (BEL) is the task of grounding entity mentions to a knowledge base.
1 code implementation • Data Analytics solutions for Real-LIfe APplications 2023 • Arik Ermshaus, Sunita Singh, Ulf Leser
Human activity recognition (HAR) systems implement workflows that automatically detect activities from motion data, captured e. g. by wearable devices such as smartphones.
2 code implementations • Advanced Analytics and Learning on Temporal Data 2023 • Arik Ermshaus, Patrick Schäfer, Ulf Leser
We provide, for the first time, a systematic survey and experimental study of 6 TS window size selection (WSS) algorithms on three diverse TSDM tasks, namely anomaly detection, segmentation and motif discovery, using state-of-the art TSDM algorithms and benchmarks.
1 code implementation • 24 Jan 2023 • Patrick Schäfer, Ulf Leser
Time series classification (TSC) is the task of assigning a time series to one of a set of predefined classes, usually based on a model learned from examples.
2 code implementations • 28 Jul 2022 • Arik Ermshaus, Patrick Schäfer, Ulf Leser
Such processes often consist of multiple states, e. g. operating modes of a machine, such that state changes in the observed processes result in changes in the distribution of shape of the measured values.
Ranked #1 on Change Point Detection on TSSB (Covering metric)
1 code implementation • 8 Jun 2022 • Patrick Schäfer, Ulf Leser
Motif discovery (MD) is the task of finding such motifs in a given input series.
2 code implementations • International Conference on Information & Knowledge Management 2021 • Patrick Schäfer, Arik Ermshaus, Ulf Leser
In our experimental evaluation using a benchmark of 98 datasets, we show that ClaSP outperforms the state-of-the-art in terms of accuracy and is also faster than the second best method.
Ranked #1 on Change Point Detection on TSSB
1 code implementation • ACL 2021 • Matthias Vogt, Ulf Leser, Alan Akbik
We define and study the task of early sexual predator detection (eSPD) in chats, where the goal is to analyze a running chat from its beginning and predict grooming attempts as early and as accurately as possible.
no code implementations • 25 Aug 2020 • Maryam Habibi, Johannes Starlinger, Ulf Leser
Tables display information as a two-dimensional matrix, the semantics of which is conveyed by a mixture of structure (rows, columns), headers, caption, and content.
2 code implementations • 17 Aug 2020 • Leon Weber, Mario Sänger, Jannes Münchmeyer, Maryam Habibi, Ulf Leser, Alan Akbik
Summary: Named Entity Recognition (NER) is an important step in biomedical information extraction pipelines.
1 code implementation • ACL 2019 • Leon Weber, Pasquale Minervini, Jannes Münchmeyer, Ulf Leser, Tim Rocktäschel
In contrast, neural models can cope very well with ambiguity by learning distributed representations of words and their composition from data, but lead to models that are difficult to interpret.
no code implementations • ICLR 2019 • Leon Weber, Pasquale Minervini, Ulf Leser, Tim Rocktäschel
Currently, most work in natural language processing focuses on neural networks which learn distributed representations of words and their composition, thereby performing well in the presence of large linguistic variability.
1 code implementation • WS 2018 • Jurica {\v{S}}eva, Martin Wackerbauer, Ulf Leser
For obtaining a realistic classification model, we propose the use of abstracts summarised in relevant sentences as unlabelled examples through Self-Training.
no code implementations • 30 May 2018 • Carl Witt, Marc Bux, Wladislaw Gusew, Ulf Leser
In many domains, the previous decade was characterized by increasing data volumes and growing complexity of computational workloads, creating new demands for highly data-parallel computing in distributed systems.
no code implementations • 4 May 2018 • Roland Roller, Madeleine Kittner, Dirk Weissenborn, Ulf Leser
Biomedical concept normalization links concept mentions in texts to a semantically equivalent concept in a biomedical knowledge base.
1 code implementation • 30 Nov 2017 • Patrick Schäfer, Ulf Leser
Multivariate time series (MTS) arise when multiple interconnected sensors record data over time.
1 code implementation • 26 Jan 2017 • Patrick Schäfer, Ulf Leser
On the popular UCR benchmark of 85 TS datasets, WEASEL is more accurate than the best current non-ensemble algorithms at orders-of-magnitude lower classification and training times, and it is almost as accurate as ensemble classifiers, whose computational complexity makes them inapplicable even for mid-size datasets.
no code implementations • LREC 2016 • Mario S{\"a}nger, Ulf Leser, Steffen Kemmerer, Peter Adolphs, Roman Klinger
This corpus consists of 1, 760 annotated application reviews from the Google Play Store with 2, 487 aspects and 3, 959 subjective phrases.