Deep neural approaches to relation triplets extraction: A comprehensive survey
The task of relation extraction is about identifying entities and relations among them in free
text for the enrichment of structured knowledge bases (KBs). In this paper, we present a …
text for the enrichment of structured knowledge bases (KBs). In this paper, we present a …
A survey on recent approaches for natural language processing in low-resource scenarios
Deep neural networks and huge language models are becoming omnipresent in natural
language applications. As they are known for requiring large amounts of training data, there …
language applications. As they are known for requiring large amounts of training data, there …
Machine Learning: Models, Challenges, and Research Directions
T Talaei Khoei, N Kaabouch - Future Internet, 2023 - mdpi.com
Machine learning techniques have emerged as a transformative force, revolutionizing
various application domains, particularly cybersecurity. The development of optimal …
various application domains, particularly cybersecurity. The development of optimal …
Research of Chinese intangible cultural heritage knowledge graph construction and attribute value extraction with graph attention network
T Fan, H Wang - Information Processing & Management, 2022 - Elsevier
The development of digital technology promotes the construction of the Intangible cultural
heritage (ICH) database but the data is still unorganized and not linked well, which makes …
heritage (ICH) database but the data is still unorganized and not linked well, which makes …
Learning to decouple relations: Few-shot relation classification with entity-guided attention and confusion-aware training
This paper aims to enhance the few-shot relation classification especially for sentences that
jointly describe multiple relations. Due to the fact that some relations usually keep high co …
jointly describe multiple relations. Due to the fact that some relations usually keep high co …
Pre-training entity relation encoder with intra-span and inter-span information
In this paper, we integrate span-related information into pre-trained encoder for entity
relation extraction task. Instead of using general-purpose sentence encoder (eg, existing …
relation extraction task. Instead of using general-purpose sentence encoder (eg, existing …
SENT: sentence-level distant relation extraction via negative training
Distant supervision for relation extraction provides uniform bag labels for each sentence
inside the bag, while accurate sentence labels are important for downstream applications …
inside the bag, while accurate sentence labels are important for downstream applications …
What do you mean by relation extraction? a survey on datasets and study on scientific relation classification
E Bassignana, B Plank - arXiv preprint arXiv:2204.13516, 2022 - arxiv.org
Over the last five years, research on Relation Extraction (RE) witnessed extensive progress
with many new dataset releases. At the same time, setup clarity has decreased, contributing …
with many new dataset releases. At the same time, setup clarity has decreased, contributing …
Revisiting the negative data of distantly supervised relation extraction
Distantly supervision automatically generates plenty of training samples for relation
extraction. However, it also incurs two major problems: noisy labels and imbalanced training …
extraction. However, it also incurs two major problems: noisy labels and imbalanced training …
Towards interpretable clinical diagnosis with Bayesian network ensembles stacked on entity-aware CNNs
J Chen, X Dai, Q Yuan, C Lu… - Proceedings of the 58th …, 2020 - aclanthology.org
The automatic text-based diagnosis remains a challenging task for clinical use because it
requires appropriate balance between accuracy and interpretability. In this paper, we …
requires appropriate balance between accuracy and interpretability. In this paper, we …