activity
20182025
most citedEnabling News Consumers to View and Understand Biased News Coverage: A Study on the Perception and Visualization of Media Bias

35 citations · 244 across the 32 of their papers we have counts for

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10 papers · 1 filter

cs.IR2023

TEIMMA: The First Content Reuse Annotator for Text, Images, and Math

Ankit Satpute, André Greiner-Petter, Moritz Schubotz +4

This demo paper presents the first tool to annotate the reuse of text, images, and mathematical formulae in a document pair -- TEIMMA. Annotating content reuse is particularly usef…

cs.IR20231 cited

Methods and Tools to Advance the Retrieval of Mathematical Knowledge from Digital Libraries for Search-, Recommendation-, and Assistance-Systems

Bela Gipp, André Greiner-Petter, Moritz Schubotz +1

This project investigated new approaches and technologies to enhance the accessibility of mathematical content and its semantic information for a broad range of information retriev…

cs.IR202322 cited

Introducing MBIB -- the first Media Bias Identification Benchmark Task and Dataset Collection

Martin Wessel, Tomáš Horych, Terry Ruas +3

Although media bias detection is a complex multi-task problem, there is, to date, no unified benchmark grouping these evaluation tasks. We introduce the Media Bias Identification B…

cs.IR20226 cited

Collaborative and AI-aided Exam Question Generation using Wikidata in Education

Philipp Scharpf, Moritz Schubotz, Andreas Spitz +2

Since the COVID-19 outbreak, the use of digital learning or education platforms has significantly increased. Teachers now digitally distribute homework and provide exercise questio…

cs.IR2022

Mining Mathematical Documents for Question Answering via Unsupervised Formula Labeling

Philipp Scharpf, Moritz Schubotz, Bela Gipp

The increasing number of questions on Question Answering (QA) platforms like Math Stack Exchange (MSE) signifies a growing information need to answer math-related questions. Howeve…

cs.IR2022

Specialized Document Embeddings for Aspect-based Similarity of Research Papers

Malte Ostendorff, Till Blume, Terry Ruas +2

Document embeddings and similarity measures underpin content-based recommender systems, whereby a document is commonly represented as a single generic embedding. However, similarit…