Found: 31
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Integrating Knowledge Graph and Machine Learning Methods for Landslide Susceptibility Assessment.
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- Remote Sensing, 2024, v. 16, n. 13, p. 2399, doi. 10.3390/rs16132399
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- Article
Developing a Base Domain Ontology from Geoscience Report Collection to Aid in Information Retrieval towards Spatiotemporal and Topic Association.
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- ISPRS International Journal of Geo-Information, 2024, v. 13, n. 1, p. 14, doi. 10.3390/ijgi13010014
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- Article
CnGeoPLM: Contextual knowledge selection and embedding with pretrained language representation model for the geoscience domain.
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- Earth Science Informatics, 2023, v. 16, n. 4, p. 3629, doi. 10.1007/s12145-023-01112-6
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- Article
An adaptive representation model for geoscience knowledge graphs considering complex spatiotemporal features and relationships.
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- SCIENCE CHINA Earth Sciences, 2023, v. 66, n. 11, p. 2563, doi. 10.1007/s11430-022-1169-9
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- Article
A Practical Approach to Constructing a Geological Knowledge Graph: A Case Study of Mineral Exploration Data.
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- Journal of Earth Science, 2023, v. 34, n. 5, p. 1374, doi. 10.1007/s12583-023-1809-3
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- Article
Ontology-Based BERT Model for Automated Information Extraction from Geological Hazard Reports.
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- Journal of Earth Science, 2023, v. 34, n. 5, p. 1390, doi. 10.1007/s12583-022-1724-z
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- Article
Extracting Named Entity Using Entity Labeling in Geological Text Using Deep Learning Approach.
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- Journal of Earth Science, 2023, v. 34, n. 5, p. 1406, doi. 10.1007/s12583-022-1789-8
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- Article
Knowledge Graph for Identifying Geological Disasters by Integrating Computer Vision with Ontology.
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- Journal of Earth Science, 2023, v. 34, n. 5, p. 1418, doi. 10.1007/s12583-022-1641-1
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- Article
Integrating NLP and Ontology Matching into a Unified System for Automated Information Extraction from Geological Hazard Reports.
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- Journal of Earth Science, 2023, v. 34, n. 5, p. 1433, doi. 10.1007/s12583-022-1716-z
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- Article
Spatio-Temporal Relevance Classification from Geographic Texts Using Deep Learning.
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- ISPRS International Journal of Geo-Information, 2023, v. 12, n. 9, p. 359, doi. 10.3390/ijgi12090359
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- Article
NeuroSPE: A neuro‐net spatial relation extractor for natural language text fusing gazetteers and pretrained models.
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- Transactions in GIS, 2023, v. 27, n. 5, p. 1526, doi. 10.1111/tgis.13086
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- Article
Construction and Application of a Knowledge Graph for Iron Deposits Using Text Mining Analytics and a Deep Learning Algorithm.
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- Mathematical Geosciences, 2023, v. 55, n. 3, p. 423, doi. 10.1007/s11004-023-10050-4
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- Article
Geographic Named Entity Recognition by Employing Natural Language Processing and an Improved BERT Model.
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- ISPRS International Journal of Geo-Information, 2022, v. 11, n. 12, p. 598, doi. 10.3390/ijgi11120598
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- Article
GeoBERTSegmenter: Word Segmentation of Chinese Texts in the Geoscience Domain Using the Improved BERT Model.
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- Earth & Space Science, 2022, v. 9, n. 10, p. 1, doi. 10.1029/2022EA002511
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- Article
Few-shot learning for name entity recognition in geological text based on GeoBERT.
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- Earth Science Informatics, 2022, v. 15, n. 2, p. 979, doi. 10.1007/s12145-022-00775-x
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- Article
ChineseTR: A weakly supervised toponym recognition architecture based on automatic training data generator and deep neural network.
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- Transactions in GIS, 2022, v. 26, n. 3, p. 1256, doi. 10.1111/tgis.12902
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- Article
Chinese toponym recognition with variant neural structures from social media messages based on BERT methods.
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- Journal of Geographical Systems, 2022, v. 24, n. 2, p. 143, doi. 10.1007/s10109-022-00375-9
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- Article
Spatially oriented convolutional neural network for spatial relation extraction from natural language texts.
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- Transactions in GIS, 2022, v. 26, n. 2, p. 839, doi. 10.1111/tgis.12887
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- Article
Chinese Named Entity Recognition in the Geoscience Domain Based on BERT.
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- Earth & Space Science, 2022, v. 9, n. 3, p. 1, doi. 10.1029/2021EA002166
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What is this article about? Generative summarization with the BERT model in the geosciences domain.
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- Earth Science Informatics, 2022, v. 15, n. 1, p. 21, doi. 10.1007/s12145-021-00695-2
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- Article
Text visualization for geological hazard documents via text mining and natural language processing.
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- Earth Science Informatics, 2022, v. 15, n. 1, p. 439, doi. 10.1007/s12145-021-00732-0
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- Article
Extraction of temporal information from social media messages using the BERT model.
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- Earth Science Informatics, 2022, v. 15, n. 1, p. 573, doi. 10.1007/s12145-021-00756-6
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- Article
DGANet: A Dilated Graph Attention-Based Network for Local Feature Extraction on 3D Point Clouds.
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- Remote Sensing, 2021, v. 13, n. 17, p. 3484, doi. 10.3390/rs13173484
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- Article
WSGAN: An Improved Generative Adversarial Network for Remote Sensing Image Road Network Extraction by Weakly Supervised Processing.
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- Remote Sensing, 2021, v. 13, n. 13, p. 2506, doi. 10.3390/rs13132506
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- Article
Chinese Word Segmentation Based on Self‐Learning Model and Geological Knowledge for the Geoscience Domain.
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- Earth & Space Science, 2021, v. 8, n. 6, p. 1, doi. 10.1029/2021EA001673
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- Article
GKEEP: An Enhanced Graph‐Based Keyword Extractor With Error‐Feedback Propagation for Geoscience Reports.
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- Earth & Space Science, 2021, v. 8, n. 5, p. 1, doi. 10.1029/2020EA001602
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- Article
Unsupervised Haze Removal for High-Resolution Optical Remote-Sensing Images Based on Improved Generative Adversarial Networks.
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- Remote Sensing, 2020, v. 12, n. 24, p. 4162, doi. 10.3390/rs12244162
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- Article
Automatic spatiotemporal and semantic information extraction from unstructured geoscience reports using text mining techniques.
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- Earth Science Informatics, 2020, v. 13, n. 4, p. 1393, doi. 10.1007/s12145-020-00527-9
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- Article
Dictionary‐Based Automated Information Extraction From Geological Documents Using a Deep Learning Algorithm.
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- Earth & Space Science, 2020, v. 7, n. 3, p. 1, doi. 10.1029/2019EA000993
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BiLSTM-CRF for geological named entity recognition from the geoscience literature.
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- Earth Science Informatics, 2019, v. 12, n. 4, p. 565, doi. 10.1007/s12145-019-00390-3
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- Article
GNER: A Generative Model for Geological Named Entity Recognition Without Labeled Data Using Deep Learning.
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- Earth & Space Science, 2019, v. 6, n. 6, p. 931, doi. 10.1029/2019EA000610
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- Article