Similarity-weighted construction of contextualized commonsense knowledge graphs for knowledge-intense argumentation tasks

M Plenz, J Opitz, P Heinisch, P Cimiano… - arXiv preprint arXiv …, 2023 - arxiv.org
Arguments often do not make explicit how a conclusion follows from its premises. To
compensate for this lack, we enrich arguments with structured background knowledge to …

Uncovering implicit inferences for improved relational argument mining

A Saadat-Yazdi, JZ Pan… - The 17th Conference of the …, 2023 - research.ed.ac.uk
Argument mining seeks to extract arguments and their structure from unstructured texts.
Identifying relations (such as attack, support, and neutral) between argumentative units is a …

Kevin: A knowledge enhanced validity and novelty classifier for arguments

A Saadat-Yazdi, X Li, S Chausson, V Belle… - Proceedings of the …, 2022 - aclanthology.org
Abstract The ArgMining 2022 Shared Task is concerned with predicting the validity and
novelty of an inference for a given premise and conclusion pair. We propose two feed …

SentenceLDA: Discriminative and Robust Document Representation with Sentence Level Topic Model

T Cha, D Lee - Proceedings of the 18th Conference of the …, 2024 - aclanthology.org
A subtle difference in context results in totally different nuances even for lexically identical
words. On the other hand, two words can convey similar meanings given a homogeneous …

Link Topics from Q&A Platforms using Wikidata: A Tool for Cross-platform Hierarchical Classification

AS Sha, BP Nunes, A Haller - Proceedings of the 15th ACM Web …, 2023 - dl.acm.org
This paper proposes a novel rule-based topic classification tool for questions on Q&A
platforms mediated by the Wikidata ontology–an open and accessible multilingual ontology …

MathKnowTopic: Creation of a Unified Knowledge Graph-Based Topic Modeling from Mathematical Text Books

M Srivani, A Murugappan, T Mala - International Conference on …, 2022 - Springer
Most of the mathematical text documents are complex to understand and so it is very difficult
to derive meaningful information from the text. In order to overcome this problem …