Search Results for author: Stefan Conrad

Found 13 papers, 3 papers with code

Citizen Involvement in Urban Planning - How Can Municipalities Be Supported in Evaluating Public Participation Processes for Mobility Transitions?

1 code implementation EMNLP (ArgMining) 2021 Julia Romberg, Stefan Conrad

In our evaluation, we achieve high macro F1 scores (0. 76 - 0. 80 for the identification of argumentative units; 0. 86 - 0. 93 for their classification) on all datasets.

Argument Mining Decision Making

Annotating Patient Information Needs in Online Diabetes Forums

no code implementations SMM4H (COLING) 2020 Julia Romberg, Jan Dyczmons, Sandra Olivia Borgmann, Jana Sommer, Markus Vomhof, Cecilia Brunoni, Ismael Bruck-Ramisch, Luis Enders, Andrea Icks, Stefan Conrad

First, the contributions were categorised according to whether they contain a diabetes-specific information need or not, which might either be a non diabetes-specific information need or no information need at all, resulting in an agreement of 0. 89 (Krippendorff’s α).

Fast Multi-Level Foreground Estimation

1 code implementation26 Jun 2020 Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling

Alpha matting aims to estimate the translucency of an object in a given image.

Matting

PyMatting: A Python Library for Alpha Matting

1 code implementation25 Mar 2020 Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling

Alpha matting describes the problem of separating the objects in the foreground from the background of an image given only a rough sketch.

Matting

HHU at SemEval-2018 Task 12: Analyzing an Ensemble-based Deep Learning Approach for the Argument Mining Task of Choosing the Correct Warrant

no code implementations SEMEVAL 2018 Matthias Liebeck, Andreas Funke, Stefan Conrad

This paper describes our participation in the SemEval-2018 Task 12 Argument Reasoning Comprehension Task which calls to develop systems that, given a reason and a claim, predict the correct warrant from two opposing options.

Argument Mining

On (Commercial) Benefits of Automatic Text Summarization Systems in the News Domain: A Case of Media Monitoring and Media Response Analysis

no code implementations3 Jan 2017 Pashutan Modaresi, Philipp Gross, Siavash Sefidrodi, Mirja Eckhof, Stefan Conrad

In this work, we present the results of a systematic study to investigate the (commercial) benefits of automatic text summarization systems in a real world scenario.

Text Summarization

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