A5089770558- Semantic Web and Ontologies
- Natural Language Processing Techniques
- Topic Modeling
- Data Quality and Management
- Biomedical Text Mining and Ontologies
- Scientific Computing and Data Management
- Research Data Management Practices
- Service-Oriented Architecture and Web Services
- Anomaly Detection Techniques and Applications
- Sociology and Education Studies
- Business Process Modeling and Analysis
- Educator Training and Historical Pedagogy
- Software Engineering Research
- Wikis in Education and Collaboration
- Advanced Graph Neural Networks
- Software Engineering Techniques and Practices
- Web Applications and Data Management
- Meta-analysis and systematic reviews
- Text and Document Classification Technologies
- Advanced Image and Video Retrieval Techniques
- Knowledge Management and Sharing
- Digital Humanities and Scholarship
- Data Management and Algorithms
- Historical Education and Society
- Image Retrieval and Classification Techniques
Bielefeld University
2017-2024
University of Oslo
2022-2024
Cognitive Research (United States)
2021
Karlsruhe Institute of Technology
2010-2015
With the rise of Semantic Web more and data become available encoded using standard RDF. RDF is faced towards machines: designed to be easily processable by machines it difficult understood casual users. Transforming into human-comprehensible text would facilitate non-experts assess this information. In paper we present a languageindependent method for extracting verbalization templates from parallel corpus data. Our based on distant-supervised simultaneous multi-relation learning frequent...
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This article describes advancements in the ongoing digital transformation materials science and engineering. It is driven by domain‐specific successes development of specialized data spaces. There an evident increasing need for standardization across various subdomains to support exchange entities. The MaterialDigital Initiative, funded German Federal Ministry Education Research, takes on a key role this context, fostering collaborative efforts establish unified space. implementation...
Ad hoc dataset retrieval is a trending topic in IR research. Methods and systems are evolving from metadata-based to content-based ones which exploit the data itself for improving accuracy but thus far lack specialized test collection. In this paper, we build release first collection ad retrieval, where content-oriented queries relevance judgments annotated by human experts who assisted with dashboard designed specifically comprehensively conveniently browsing both metadata of dataset. We...
Evidence-based medicine propagates that medical/clinical decisions are made by taking into account high-quality evidence, most notably in the form of randomized clinical trials. decision-making requires aggregating evidence available multiple trials to reach -by means systematic reviews- a conclusive recommendation on which treatment is best suited for given patient population. However, it challenging produce reviews keep up with ever-growing number published Therefore, new computational...
Over 80% of entities on the Semantic Web lack a human-readable label. This hampers ability any tool that uses linked data to offer meaningful interface human users. We argue methods for deriving labels are essential in order allow usage Data. In this paper we explore, implement, and evaluate method based variable names used large corpus SPARQL queries built from set log files. analyze structure graph patterns classification scheme patterns. Based classification, identify us derive useful...
Link Prediction(LP) is an essential task over Knowledge Graphs(KGs), traditionally focussed on using and predicting the relations between entities. Textual entity descriptions have already been shown to be valuable, but models that incorporate numerical literals minor improvements existing benchmark datasets. It unclear whether a model actually better in literals, or capable of utilizing graph structure. This raises doubts about effectiveness these methods suitability We propose methodology...
OTTR is a language for representing ontology modeling patterns, which enables to build ontologies or knowledge bases by instantiating templates. Thereby, particularities of the ontological representation are hidden from domain experts, and it engineers to, some extent, separate processes deciding about what information model how information, e.g., design patterns use. Certain decisions can thus be postponed benefit focusing on one these processes. To date, only few works engineering where...
Representing provenance information for data is of crucial importance reuse. This in particular the case language resources such as annotated corpora. NIF has been proposed an RDF vocabulary to support representation text together with annotations. However, suffer s from severe shortcomings respect its ability represent information. As a remedy this, we present MOND, new glue ontology that implements interface between and PROV-O inclusion into datasets. We first approach reifies annotations...
Knowledge Graphs are relevant for many applications, but inherently incomplete. Thus, Link Prediction methods have been proposed to infer new triples in order complete a given Graph. Many ignore literals, spite of the fact that literals can express important information about entities not encoded relations between entities. The existing do incorporate literal (e. g., LiteralE) introduce complex architectures by modifying model or loss-function. In our research paper, we propose approach...