Results 11 to 20 of about 3,127 (217)
A survey on Relation Extraction
Intelligent Systems with Applications, 2023 With the advent of the Internet, the daily production of digital text in the form of social media, emails, blogs, news items, books, research papers, and Q&A forums has increased significantly.
Kartik Detroja +2 more
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Multi-Attribute Relation Extraction (MARE): Simplifying the Application of Relation Extraction [PDF]
Proceedings of the 2nd International Conference on Deep Learning Theory and Applications, 2021 Preprint of short paper for the 2nd International Conference on Deep Learning Theory and Applications (2021)
Lars Klöser +3 more
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Relation Extraction with Explanation [PDF]
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020 Recent neural models for relation extraction with distant supervision alleviate the impact of irrelevant sentences in a bag by learning importance weights for the sentences. Efforts thus far have focused on improving extraction accuracy but little is known about their explainability.
Hamed Shahbazi +3 more
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Multilingual Relation Extraction: A Survey
IEEE AccessRelation extraction plays a fundamental role in applications of various research fields such as knowledge graph construction, event extraction, and question answering over knowledge graphs, as they often rely on extracting relationships between named ...
Manzoor Ali +5 more
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Relational autoencoder for feature extraction [PDF]
2017 International Joint Conference on Neural Networks (IJCNN), 2017 Feature extraction becomes increasingly important as data grows high dimensional. Autoencoder as a neural network based feature extraction method achieves great success in generating abstract features of high dimensional data. However, it fails to consider the relationships of data samples which may affect experimental results of using original and new
Qinxue Meng +3 more
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Global Relation Embedding for Relation Extraction [PDF]
Proceedings of the 2018 Conference of the North American Chapter of
the Association for Computational Linguistics: Human Language
Technologies, Volume 1 (Long Papers), 2018 We study the problem of textual relation embedding with distant supervision. To combat the wrong labeling problem of distant supervision, we propose to embed textual relations with global statistics of relations, i.e., the co-occurrence statistics of textual and knowledge base relations collected from the entire corpus.
Yu Su 0001 +5 more
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Dialogue-Based Relation Extraction [PDF]
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020 To appear in ACL ...
Dian Yu 0001 +3 more
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Review of Text-Oriented Entity Relation Extraction Research [PDF]
Jisuanji kexue yu tansuoInformation extraction is the foundation of knowledge graph construction, and relation extraction, as a key process and core step of information extraction, aims to locate entities from text data and recognize semantic links between entities.
REN Anqi, LIU Lin, WANG Hailong, LIU Jing
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EANT: Distant Supervision for Relation Extraction with Entity Attributes via Negative Training
Applied Sciences, 2022 Distant supervision for relation extraction (DSRE) automatically acquires large-scale annotated data by aligning the corpus with the knowledge base, which dramatically reduces the cost of manual annotation.
Xuxin Chen, Xinli Huang
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Relation Extraction : A Survey
CoRR, 2017 With the advent of the Internet, large amount of digital text is generated everyday in the form of news articles, research publications, blogs, question answering forums and social media. It is important to develop techniques for extracting information automatically from these documents, as lot of important information is hidden within them.
Sachin Pawar +2 more
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