527 citations · 605 across the 12 of their papers we have counts for
13 papers
Insights from an OTTR-centric Ontology Engineering Methodology
Moritz Blum, Basil Ell, Philipp Cimiano
OTTR is a language for representing ontology modeling patterns, which enables to build ontologies or knowledge bases by instantiating templates. Thereby, particularities of the ont…
The Ecological Fallacy in Annotation: Modelling Human Label Variation goes beyond Sociodemographics
Matthias Orlikowski, Paul Röttger, Philipp Cimiano +1
Many NLP tasks exhibit human label variation, where different annotators give different labels to the same texts. This variation is known to depend, at least in part, on the sociod…
Similarity-weighted Construction of Contextualized Commonsense Knowledge Graphs for Knowledge-intense Argumentation Tasks
Moritz Plenz, Juri Opitz, Philipp Heinisch +2
Arguments often do not make explicit how a conclusion follows from its premises. To compensate for this lack, we enrich arguments with structured background knowledge to support kn…
Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
Milad Alshomary, Timon Gurcke, Shahbaz Syed +5
Key point analysis is the task of extracting a set of concise and high-level statements from a given collection of arguments, representing the gist of these arguments. This paper p…
Zero-Shot Cross-Lingual Opinion Target Extraction
Soufian Jebbara, Philipp Cimiano
Aspect-based sentiment analysis involves the recognition of so called opinion target expressions (OTEs). To automatically extract OTEs, supervised learning algorithms are usually e…
Evaluating Architectural Choices for Deep Learning Approaches for Question Answering over Knowledge Bases
Sherzod Hakimov, Soufian Jebbara, Philipp Cimiano
The task of answering natural language questions over knowledge bases has received wide attention in recent years. Various deep learning architectures have been proposed for this t…
AMUSE: Multilingual Semantic Parsing for Question Answering over Linked Data
Sherzod Hakimov, Soufian Jebbara, Philipp Cimiano
The task of answering natural language questions over RDF data has received wide interest in recent years, in particular in the context of the series of QALD benchmarks. The task c…
Predicting Disease-Gene Associations using Cross-Document Graph-based Features
Hendrik ter Horst, Matthias Hartung, Roman Klinger +2
In the context of personalized medicine, text mining methods pose an interesting option for identifying disease-gene associations, as they can be used to generate novel links betwe…
Improving Opinion-Target Extraction with Character-Level Word Embeddings
Soufian Jebbara, Philipp Cimiano
Fine-grained sentiment analysis is receiving increasing attention in recent years. Extracting opinion target expressions (OTE) in reviews is often an important step in fine-grained…
Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture
Soufian Jebbara, Philipp Cimiano
The World Wide Web holds a wealth of information in the form of unstructured texts such as customer reviews for products, events and more. By extracting and analyzing the expressed…
Aspect-Based Relational Sentiment Analysis Using a Stacked Neural Network Architecture
Soufian Jebbara, Philipp Cimiano
Sentiment analysis can be regarded as a relation extraction problem in which the sentiment of some opinion holder towards a certain aspect of a product, theme or event needs to be…
Opinion Mining in Online Reviews About Distance Education Programs
Janik Jaskolski, Fabian Siegberg, Thomas Tibroni +2
The popularity of distance education programs is increasing at a fast pace. En par with this development, online communication in fora, social media and reviewing platforms between…
Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis
P. Cimiano, A. Hotho, S. Staab
We present a novel approach to the automatic acquisition of taxonomies or concept hierarchies from a text corpus. The approach is based on Formal Concept Analysis (FCA), a method m…