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MEduKG: A Deep-Learning-Based Approach for Multi-Modal Educational Knowledge Graph Construction
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In: Information; Volume 13; Issue 2; Pages: 91 (2022)
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| 2 |
Analysis of the Full-Size Russian Corpus of Internet Drug Reviews with Complex NER Labeling Using Deep Learning Neural Networks and Language Models
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In: Applied Sciences; Volume 12; Issue 1; Pages: 491 (2022)
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| 3 |
Contextual Semantic-Guided Entity-Centric GCN for Relation Extraction
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In: Mathematics; Volume 10; Issue 8; Pages: 1344 (2022)
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| 4 |
Extraction of the Relations among Significant Pharmacological Entities in Russian-Language Reviews of Internet Users on Medications
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 10 (2022)
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| 5 |
Exploring Construction of a Company Domain-Specific Knowledge Graph from Financial Texts Using Hybrid Information Extraction
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Jen, Chun-Heng. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021
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| 6 |
DiS-ReX: A Multilingual Dataset for Distantly Supervised Relation Extraction ...
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| 7 |
DiS-ReX: A Multilingual Dataset for Distantly Supervised Relation Extraction ...
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| 8 |
KGGCN: Knowledge-Guided Graph Convolutional Networks for Distantly Supervised Relation Extraction
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In: Applied Sciences ; Volume 11 ; Issue 16 (2021)
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| 9 |
Extracting Semantic Relationships in Greek Literary Texts
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In: Sustainability ; Volume 13 ; Issue 16 (2021)
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| 10 |
MRE: A Military Relation Extraction Model Based on BiGRU and Multi-Head Attention
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In: Symmetry ; Volume 13 ; Issue 9 (2021)
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| 11 |
Few-Shot Relation Extraction on Ancient Chinese Documents
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In: Applied Sciences; Volume 11; Issue 24; Pages: 12060 (2021)
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| 12 |
Causality Mining in Natural Languages Using Machine and Deep Learning Techniques: A Survey
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In: Applied Sciences ; Volume 11 ; Issue 21 (2021)
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| 13 |
K-EPIC: Entity-Perceived Context Representation in Korean Relation Extraction
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In: Applied Sciences; Volume 11; Issue 23; Pages: 11472 (2021)
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Abstract:
Relation Extraction (RE) aims to predict the correct relation between two entities from the given sentence. To obtain the proper relation in Relation Extraction (RE), it is significant to comprehend the precise meaning of the two entities as well as the context of the sentence. In contrast to the RE research in English, Korean-based RE studies focusing on the entities and preserving Korean linguistic properties rarely exist. Therefore, we propose K-EPIC (Entity-Perceived Context representation in Korean) to ensure enhanced capability for understanding the meaning of entities along with considering linguistic characteristics in Korean. We present the experimental results on the BERT-Ko-RE and KLUE-RE datasets with four different types of K-EPIC methods, utilizing entity position tokens. To compare the ability of understanding entities and context of Korean pre-trained language models, we analyze HanBERT, KLUE-BERT, KoBERT, KorBERT, KoELECTRA, and multilingual-BERT (mBERT). The experimental results demonstrate that the F1 score increases significantly with our K-EPIC and that the performance of the language models trained with the Korean corpus outperforms the baseline.
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Keyword:
deep learning; information extraction; Korean pre-trained language model; relation extraction
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URL: https://doi.org/10.3390/app112311472
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| 14 |
"Is depression related to cannabis?": A Knowledge-infused Model for Entity and Relation Extraction with Limited Supervision
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In: Publications (2021)
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| 15 |
BioSGAN: Protein-phenotype Co-mention classification using semi-supervised generative adversarial networks
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In: UNF Faculty Publications (2021)
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| 16 |
A Thesaurus Based Semantic Relation Extraction for Agricultural Corpora
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In: IFIP Advances in Information and Communication Technology ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS) ; https://hal.inria.fr/hal-03434803 ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS), Feb 2020, Chennai, India. pp.99-111, ⟨10.1007/978-3-030-63467-4_8⟩ (2020)
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| 17 |
Prerequisites for Extracting Entity Relations from Swedish Texts
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Lenas, Erik. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020
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| 18 |
Natural Language Processing Model for Automatic Analysis of Cybersecurity-Related Documents
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In: Symmetry ; Volume 12 ; Issue 3 (2020)
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| 19 |
Dual Pointer Network for Fast Extraction of Multiple Relations in a Sentence
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In: Applied Sciences ; Volume 10 ; Issue 11 (2020)
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| 20 |
Semi-Automatic Corpus Expansion and Extraction of Uyghur-Named Entities and Relations Based on a Hybrid Method
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In: Information ; Volume 11 ; Issue 1 (2020)
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