Results 41 to 50 of about 353,852 (269)
Distantly Supervised Named Entity Recognition with Self-Adaptive Label Correction
Applied Sciences, 2022 Named entity recognition has achieved remarkable success on benchmarks with high-quality manual annotations. Such annotations are labor-intensive and time-consuming, thus unavailable in real-world scenarios.
Binling Nie, Chenyang Li
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Distant Supervision for Tweet Classification Using YouTube Labels
Proceedings of the International AAAI Conference on Web and Social Media, 2021 We study an approach to tweet classification based on distant supervision, whereby we automatically transfer labels from one social medium to another. In particular, we apply classes assigned to YouTube videos to tweets linking to these videos. This provides for free a virtually unlimited number of labelled instances that can be used as
Magdy W +3 more
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Adaptive Named Entity Recognition Using Distant Supervision for Contemporary Written Texts
IEEE Access, 2021 Named entity recognition (NER) is the process of categorizing named entities in a given text that suffers from the lack of labeled corpora, which is a long-standing issue. Deep neural networks have been successfully applied to NER tasks.
Juae Kim +3 more
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Global Relation Embedding for Relation Extraction
, 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 ...
Gur, Izzeddin +5 more
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Improving distant supervision using inference learning [PDF]
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), 2015 Distant supervision is a widely applied approach to automatic training of relation extraction systems and has the advantage that it can generate large amounts of labelled data with minimal effort. However, this data may contain errors and consequently systems trained using distant supervision tend not to perform as well as those based on manually ...
Roller, R.A. +3 more
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Multi-factor person entity relation extraction model based on distant supervision
Tongxin xuebao, 2018 Aiming at the problem that the basic assumption of distant supervision was too strong and easy to produce noise data,a model of the person entity relation extraction which could automatically filter the training data generated by distant supervision was ...
Yangchen HUANG +5 more
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A Neural Relation Extraction Model for Distant Supervision in Counter-Terrorism Scenario
IEEE Access, 2020 Natural language processing (NLP) is the best solution to extensive, unstructured, complex, and diverse network big data for counter-terrorism. Through the text analysis, it is the basis and the most critical step to quickly extract the relationship ...
Jiaqi Hou +5 more
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Spatial relation learning in complementary scenarios with deep neural networks
Frontiers in Neurorobotics, 2022 A cognitive agent performing in the real world needs to learn relevant concepts about its environment (e.g., objects, color, and shapes) and react accordingly.
Jae Hee Lee +6 more
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International Journal of Digital Earth, 2022 Earth observations, especially satellite data, have produced a wealth of methods and results in meeting global challenges, often presented in unstructured texts such as papers or reports.
Ming Lin, Meng Jin, Yufu Liu, Yuqi Bai
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, 2017 NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment analysis and related tasks, researchers have therefore used binarized emoticons and specific hashtags as forms of distant supervision.
Felbo, Bjarke +4 more
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