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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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Analyzing COVID-19 Medical Papers Using Artificial Intelligence: Insights for Researchers and Medical Professionals
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 4 (2022)
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A Multi-Entity Knowledge Joint Extraction Method of Communication Equipment Faults for Industrial IoT
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In: Electronics; Volume 11; Issue 7; Pages: 979 (2022)
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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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Word Sense Disambiguation Using Prior Probability Estimation Based on the Korean WordNet
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In: Electronics; Volume 10; Issue 23; Pages: 2938 (2021)
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Abstract:
Supervised disambiguation using a large amount of corpus data delivers better performance than other word sense disambiguation methods. However, it is not easy to construct large-scale, sense-tagged corpora since this requires high cost and time. On the other hand, implementing unsupervised disambiguation is relatively easy, although most of the efforts have not been satisfactory. A primary reason for the performance degradation of unsupervised disambiguation is that the semantic occurrence probability of ambiguous words is not available. Hence, a data deficiency problem occurs while determining the dependency between words. This paper proposes an unsupervised disambiguation method using a prior probability estimation based on the Korean WordNet. This performs better than supervised disambiguation. In the Korean WordNet, all the words have similar semantic characteristics to their related words. Thus, it is assumed that the dependency between words is the same as the dependency between their related words. This resolves the data deficiency problem by determining the dependency between words by calculating the χ2 statistic between related words. Moreover, in order to have the same effect as using the semantic occurrence probability as prior probability, which is used in supervised disambiguation, semantically related words of ambiguous vocabulary are obtained and utilized as prior probability data. An experiment was conducted with Korean, English, and Chinese to evaluate the performance of our proposed lexical disambiguation method. We found that our proposed method had better performance than supervised disambiguation methods even though our method is based on unsupervised disambiguation (using a knowledge-based approach).
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Keyword:
data mining; information extraction; knowledge-based model; Korean WordNet; word sense disambiguation
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URL: https://doi.org/10.3390/electronics10232938
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| 6 |
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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Development of Knowledge Base Using Human Experience Semantic Network for Instructive Texts
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In: Applied Sciences ; Volume 11 ; Issue 17 (2021)
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| 8 |
"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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| 9 |
Relational concept analysis: a polyvalent tool for knowledge extraction ; Analyse relationnelle de concepts : une méthode polyvalente pour l'extraction de connaissance
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In: https://hal.archives-ouvertes.fr/tel-03042085 ; Informatique [cs]. Université du Québec à Montréal; Université de Lorraine, 2020. Français. ⟨NNT : 2020LORR0136⟩ (2020)
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| 11 |
Domain-Independent Extraction of Scientific Concepts from Research Articles ...
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A computational ecosystem to support eHealth Knowledge Discovery technologies in Spanish
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NormCo: Deep Disease Normalization for Biomedical Knowledge Base Construction
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In: Wright, Dustin. (2019). NormCo: Deep Disease Normalization for Biomedical Knowledge Base Construction. UC San Diego: Computer Science and Engineering. Retrieved from: http://www.escholarship.org/uc/item/3410q7zk (2019)
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Engineering an aligned gold-standard corpus of human to machine oriented Controlled Natural Language
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When humans and machines collaborate: Cross-lingual Label Editing in Wikidata ...
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When humans and machines collaborate: Cross-lingual Label Editing in Wikidata ...
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Personnalisation et enrichissement des méthodes d’accès aux données
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In: https://hal.inria.fr/tel-01739707 ; Base de données [cs.DB]. Université Rennes 1, 2018 (2018)
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Knowledge Base Population based on Entity Graph Analysis ; Peuplement d'une base de connaissance fondé sur l'exploitation d'un graphe d'entités
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In: https://tel.archives-ouvertes.fr/tel-01810983 ; Computation and Language [cs.CL]. Université Paris Saclay (COmUE), 2018. English. ⟨NNT : 2018SACLS092⟩ (2018)
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Fictive motion extraction and classification
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In: ISSN: 1365-8816 ; EISSN: 1365-8824 ; International Journal of Geographical Information Science ; https://hal.archives-ouvertes.fr/hal-02139019 ; International Journal of Geographical Information Science, Taylor & Francis, 2018, 32 (11), pp.2247-2271. ⟨10.1080/13658816.2018.1498503⟩ (2018)
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