Results 41 to 50 of about 356,474 (267)
Semi-supervised Stance Detection of Tweets Via Distant Network Supervision [PDF]
Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 2022 Detecting and labeling stance in social media text is strongly motivated by hate speech detection, poll prediction, engagement forecasting, and concerted propaganda detection. Today's best neural stance detectors need large volumes of training data, which is difficult to curate given the fast-changing landscape of social media text and issues on which ...
Dutta, Subhabrata +3 more
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IEEE Access, 2020 Recent advances in deep neural networks (DNNs) have enabled us to achieve reliable named entity recognition (NER) models without handcrafting features. However, these are also some obstacles imposed by using those machine learning methods, in need of a ...
Dezheng Zhang +6 more
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Distant Supervision for Sentiment Attitude Extraction
Proceedings - Natural Language Processing in a Deep Learning World, 2019 © 2019 Association for Computational Linguistics (ACL). All rights reserved. News articles often convey attitudes between the mentioned subjects, which is essential for understanding the described situation. In this paper, we describe a new approach to distant supervision for extracting sentiment attitudes between named entities mentioned in texts. Two
Rusnachenko N. +2 more
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Visual Distant Supervision for Scene Graph Generation [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Scene graph generation aims to identify objects and their relations in images, providing structured image representations that can facilitate numerous applications in computer vision. However, scene graph models usually require supervised learning on large quantities of labeled data with intensive human annotation.
Yao, Yuan +7 more
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Boosting Knowledge Base Automatically via Few-Shot Relation Classification
Frontiers in Neurorobotics, 2020 Relation classification (RC) aims at extracting structural information, i.e., triplets of two entities with a relation, from free texts, which is pivotal for automatic knowledge base construction. In this paper, we investigate a fully automatic method to
Ning Pang +3 more
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Distant Supervision for Relation Extraction with Ranking-Based Methods
Entropy, 2016 Relation extraction has benefited from distant supervision in recent years with the development of natural language processing techniques and data explosion.
Yang Xiang +3 more
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Mapping ESG Trends by Distant Supervision of Neural Language Models
Machine Learning and Knowledge Extraction, 2020 The integration of Environmental, Social and Governance (ESG) considerations into business decisions and investment strategies have accelerated over the past few years. It is important to quantify the extent to which ESG-related conversations are carried
Natraj Raman +2 more
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Iterative Annotation of Biomedical NER Corpora with Deep Neural Networks and Knowledge Bases
Applied Sciences, 2022 The large availability of clinical natural language documents, such as clinical narratives or diagnoses, requires the definition of smart automatic systems for their processing and analysis, but the lack of annotated corpora in the biomedical domain ...
Stefano Silvestri +2 more
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Adversarial Learning for Distant Supervised Relation Extraction [PDF]
Computers, Materials & Continua, 2018 Recently, many researchers have concentrated on using neural networks to learn features for Distant Supervised Relation Extraction (DSRE). These approaches generally use a softmax classifier with cross-entropy loss, which inevitably brings the noise of artificial class NA into classification process.
Zeng, Daojian +4 more
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An Attention-Based Model Using Character Composition of Entities in Chinese Relation Extraction
Information, 2020 Relation extraction is a vital task in natural language processing. It aims to identify the relationship between two specified entities in a sentence. Besides information contained in the sentence, additional information about the entities is verified to
Xiaoyu Han +3 more
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