Search Results for author:
Found 16 papers, 7 papers with code
The Media Bias Taxonomy: A Systematic Literature Review on the Forms and Automated Detection of Media Bias
However, we have identified a lack of interdisciplinarity in existing projects, and a need for more awareness of the various types of media bias to support methodologically thorough performance evaluations of media bias detection systems.
TEIMMA: The First Content Reuse Annotator for Text, Images, and Math
This demo paper presents the first tool to annotate the reuse of text, images, and mathematical formulae in a document pair -- TEIMMA.
Methods and Tools to Advance the Retrieval of Mathematical Knowledge from Digital Libraries for Search-, Recommendation-, and Assistance-Systems
This project investigated new approaches and technologies to enhance the accessibility of mathematical content and its semantic information for a broad range of information retrieval applications.
A Benchmark of PDF Information Extraction Tools using a Multi-Task and Multi-Domain Evaluation Framework for Academic Documents
Using the new framework, we benchmark ten freely available tools in extracting document metadata, bibliographic references, tables, and other content elements from academic PDF documents.
Recommending Research Papers to Chemists: A Specialized Interface for Chemical Entity Exploration
For example, in the field of biomedicine and chemistry, researchers are not only interested in textual relevance but may also want to discover or compare the contained chemical entity information found in a paper's full text.
TASSY -- A Text Annotation Survey System
We present a free and open-source tool for creating web-based surveys that include text annotation tasks.
Detecting Cross-Language Plagiarism using Open Knowledge Graphs
Identifying cross-language plagiarism is challenging, especially for distant language pairs and sense-for-sense translations.
Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection
We expect that evaluating a broad spectrum of datasets and models will benefit future research in developing misinformation detection systems.
Incorporating Word Sense Disambiguation in Neural Language Models
We present two supervised (pre-)training methods to incorporate gloss definitions from lexical resources into neural language models (LMs).
Analyzing Non-Textual Content Elements to Detect Academic Plagiarism
Analyzing non-textual content complements text-based detection approaches and increases the detection effectiveness, particularly for disguised forms of academic plagiarism.
Are Neural Language Models Good Plagiarists? A Benchmark for Neural Paraphrase Detection
The rise of language models such as BERT allows for high-quality text paraphrasing.
Identifying Machine-Paraphrased Plagiarism
Employing paraphrasing tools to conceal plagiarized text is a severe threat to academic integrity.
A First Step Towards Content Protecting Plagiarism Detection
Plagiarism detection systems are essential tools for safeguarding academic and educational integrity.
Classification and Clustering of arXiv Documents, Sections, and Abstracts, Comparing Encodings of Natural and Mathematical Language
In this paper, we show how selecting and combining encodings of natural and mathematical language affect classification and clustering of documents with mathematical content.
Mathematical Formulae in Wikimedia Projects 2020
This poster summarizes our contributions to Wikimedia's processing pipeline for mathematical formulae.
Improving Academic Plagiarism Detection for STEM Documents by Analyzing Mathematical Content and Citations
Overall, we show that analyzing the similarity of mathematical content and academic citations is a striking supplement for conventional text-based detection approaches for academic literature in the STEM disciplines.
