Machine knowledge: Creation and curation of comprehensive knowledge bases

G Weikum, XL Dong, S Razniewski… - … and Trends® in …, 2021 - nowpublishers.com
Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

A brief overview of universal sentence representation methods: A linguistic view

R Li, X Zhao, MF Moens - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
How to transfer the semantic information in a sentence to a computable numerical
embedding form is a fundamental problem in natural language processing. An informative …

Argument mining: A survey

J Lawrence, C Reed - Computational Linguistics, 2020 - direct.mit.edu
Argument mining is the automatic identification and extraction of the structure of inference
and reasoning expressed as arguments presented in natural language. Understanding …

Fake news stance detection using deep learning architecture (CNN-LSTM)

M Umer, Z Imtiaz, S Ullah, A Mehmood, GS Choi… - IEEE …, 2020 - ieeexplore.ieee.org
Society and individuals are negatively influenced both politically and socially by the
widespread increase of fake news either way generated by humans or machines. In the era …

A retrospective analysis of the fake news challenge stance detection task

A Hanselowski, A PVS, B Schiller, F Caspelherr… - arxiv preprint arxiv …, 2018 - arxiv.org
The 2017 Fake News Challenge Stage 1 (FNC-1) shared task addressed a stance
classification task as a crucial first step towards detecting fake news. To date, there is no in …

[PDF][PDF] Five years of argument mining: A data-driven analysis.

E Cabrio, S Villata - IJCAI, 2018 - ijcai.org
Argument mining is the research area aiming at extracting natural language arguments and
their relations from text, with the final goal of providing machine-processable structured data …

[HTML][HTML] Enhancing argumentative writing with automated feedback and social comparison nudging

T Wambsganss, A Janson, JM Leimeister - Computers & Education, 2022 - Elsevier
The advantages offered by natural language processing (NLP) and machine learning
enable students to receive automated feedback on their argumentation skills, independent …

ArgueTutor: An adaptive dialog-based learning system for argumentation skills

T Wambsganss, T Kueng, M Soellner… - Proceedings of the 2021 …, 2021 - dl.acm.org
Techniques from Natural-Language-Processing offer the opportunities to design new dialog-
based forms of human-computer interaction as well as to analyze the argumentation quality …

Cross-topic argument mining from heterogeneous sources using attention-based neural networks

C Stab, T Miller, I Gurevych - arxiv preprint arxiv:1802.05758, 2018 - arxiv.org
Argument mining is a core technology for automating argument search in large document
collections. Despite its usefulness for this task, most current approaches to argument mining …

Neural end-to-end learning for computational argumentation mining

S Eger, J Daxenberger, I Gurevych - arxiv preprint arxiv:1704.06104, 2017 - arxiv.org
We investigate neural techniques for end-to-end computational argumentation mining (AM).
We frame AM both as a token-based dependency parsing and as a token-based sequence …