Acronym identification and disambiguation shared tasks for scientific document understanding

APB Veyseh, F Dernoncourt, TH Nguyen… - arXiv preprint arXiv …, 2020 - arxiv.org
Acronyms are the short forms of longer phrases and they are frequently used in writing,
especially scholarly writing, to save space and facilitate the communication of information …

A survey on deep learning event extraction: Approaches and applications

Q Li, J Li, J Sheng, S Cui, J Wu, Y Hei… - … on Neural Networks …, 2022 - ieeexplore.ieee.org
Event extraction (EE) is a crucial research task for promptly apprehending event information
from massive textual data. With the rapid development of deep learning, EE based on deep …

Event detection: Gate diversity and syntactic importance scoresfor graph convolution neural networks

VD Lai, TN Nguyen, TH Nguyen - arXiv preprint arXiv:2010.14123, 2020 - arxiv.org
Recent studies on event detection (ED) haveshown that the syntactic dependency graph
canbe employed in graph convolution neural net-works (GCN) to achieve state-of-the-art per …

Graph convolutional networks for event causality identification with rich document-level structures

MT Phu, TH Nguyen - Proceedings of the 2021 conference of the …, 2021 - aclanthology.org
We study the problem of Event Causality Identification (ECI) to detect causal relation
between event mention pairs in text. Although deep learning models have recently shown …

Improving aspect-based sentiment analysis with gated graph convolutional networks and syntax-based regulation

APB Veyseh, N Nour, F Dernoncourt, QH Tran… - arXiv preprint arXiv …, 2020 - arxiv.org
Aspect-based Sentiment Analysis (ABSA) seeks to predict the sentiment polarity of a
sentence toward a specific aspect. Recently, it has been shown that dependency trees can …

Extensively matching for few-shot learning event detection

VD Lai, F Dernoncourt, TH Nguyen - arXiv preprint arXiv:2006.10093, 2020 - arxiv.org
Current event detection models under super-vised learning settings fail to transfer to
newevent types. Few-shot learning has not beenexplored in event detection even though it …

What does this acronym mean? introducing a new dataset for acronym identification and disambiguation

APB Veyseh, F Dernoncourt, QH Tran… - arXiv preprint arXiv …, 2020 - arxiv.org
Acronyms are the short forms of phrases that facilitate conveying lengthy sentences in
documents and serve as one of the mainstays of writing. Due to their importance, identifying …

[PDF][PDF] Survey on graph embeddings and their applications to machine learning problems on graphs

I Makarov, D Kiselev, N Nikitinsky, L Subelj - PeerJ Computer Science, 2021 - peerj.com
Dealing with relational data always required significant computational resources, domain
expertise and task-dependent feature engineering to incorporate structural information into a …

Introducing syntactic structures into target opinion word extraction with deep learning

APB Veyseh, N Nouri, F Dernoncourt, D Dou… - arXiv preprint arXiv …, 2020 - arxiv.org
Targeted opinion word extraction (TOWE) is a sub-task of aspect based sentiment analysis
(ABSA) which aims to find the opinion words for a given aspect-term in a sentence. Despite …

Towards generative event factuality prediction

J Murzaku, T Osborne, A Aviram… - Findings of the …, 2023 - aclanthology.org
We present a novel end-to-end generative task and system for predicting event factuality
holders, targets, and their associated factuality values. We perform the first experiments …