activity
20192022
most citedA Survey on Data Augmentation for Text Classification

422 citations · 610 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2022★ 1 cited

Reducing Information Overload: Because Even Security Experts Need to Blink

Philipp Kuehn, Markus Bayer, Tobias Frey +2

Computer Emergency Response Teams (CERTs) face increasing challenges processing the growing volume of security-related information. Daily manual analysis of threat reports, securit…

cs.CL2021★ 422 cited

A Survey on Data Augmentation for Text Classification

Markus Bayer, Marc-André Kaufhold, Christian Reuter

Data augmentation, the artificial creation of training data for machine learning by transformations, is a widely studied research field across machine learning disciplines. While i…

cs.CL2021★ 148 cited

Data Augmentation in Natural Language Processing: A Novel Text Generation Approach for Long and Short Text Classifiers

Markus Bayer, Marc-André Kaufhold, Björn Buchhold +3

In many cases of machine learning, research suggests that the development of training data might have a higher relevance than the choice and modelling of classifiers themselves. Th…

cs.CY2020★ 38 cited

Empirical Insights for Designing Information and Communication Technology for International Disaster Response

Milan Stute, Max Maass, Tom Schons +3

Due to the increase in natural disasters in the past years, Disaster Response Organizations (DROs) are faced with the challenge of coping with more and larger operations. Currently…

cs.SI2019★ 1 cited

Cross-Media Usage of Social Big Data for Emergency Services and Volunteer Communities: Approaches, Development and Challenges of Multi-Platform Social Media Services

Marc-André Kaufhold, Christian Reuter, Thomas Ludwig

The use of social media is ubiquitous and nowadays well-established in our everyday life, but increasingly also before, during or after emergencies. The produced data is spread acr…