Results 181 to 190 of about 292 (213)
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Curriculum Learning for Distant Supervision Relation Extraction
SSRN Electronic Journal, 2020Abstract Relation extraction under distant supervision leverages the existing knowledge base to label data automatically, thus greatly reduced the consumption of human labors. Although distant supervision is an efficient method to obtain a large amount of labeled data, the training dataset labeled by distant supervision suffers from noise problem ...
Qiongxin Liu +3 more
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Global Distant Supervision for Relation Extraction
Proceedings of the AAAI Conference on Artificial Intelligence, 2016Machine learning approaches to relation extraction are typically supervised and require expensive labeled data. To break the bottleneck of labeled data, a promising approach is to exploit easily obtained indirect supervision knowledge – which we usually refer to as distant supervision (DS).
Xianpei Han, Le Sun 0001
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A survey of noise reduction methods for distant supervision
Proceedings of the 2013 workshop on Automated knowledge base construction, 2013We survey recent approaches to noise reduction in distant supervision learning for relation extraction. We group them according to the principles they are based on: at-least-one constraints, topic-based models, or pattern correlations. Besides describing them, we illustrate the fundamental differences and attempt to give an outlook to potentially ...
Benjamin Roth 0001 +3 more
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Distant Supervision for Chinese Temporal Tagging
2018Temporal tagging plays an important role in many tasks such as event extraction and reasoning. Extracting Chinese temporal expressions is challenging because of the diversity of time phrases in Chinese. Usually researchers use rule-based methods or learning-based methods to extract temporal expressions. Rule-based methods can often achieve good results
Hualong Zhang +3 more
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Combining Distant and Partial Supervision for Relation Extraction
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2014Broad-coverage relation extraction either requires expensive supervised training data, or suffers from drawbacks inherent to distant supervision. We present an approach for providing partial supervision to a distantly supervised relation extractor using a small number of carefully selected examples.
Gabor Angeli +3 more
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Distant Supervision for Relation Extraction with Matrix Completion
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2014The essence of distantly supervised relation extraction is that it is an incomplete multi-label classification problem with sparse and noisy features. To tackle the sparsity and noise challenges, we propose solving the classification problem using matrix completion on factorized matrix of minimized rank.
Miao Fan +5 more
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DISTANT SUPERVISION FOR CANCER PATHWAY EXTRACTION FROM TEXT [PDF]
Biocomputing 2015, 2014 Biological pathways are central to understanding complex diseases such as cancer. The majority of this knowledge is scattered in the vast and rapidly growing research literature. To automate knowledge extraction, machine learning approaches typically require annotated examples, which are expensive and time-consuming to acquire. Recently, there has been
Hoifung Poon +2 more
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Similarity-based Distant Supervision for Definition Retrieval
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017Recognizing definition sentences from free text corpora often requires hand-crafted patterns or explicitly labeled training instances. We present a distant supervision approach addressing this challenge without using explicitly labeled data. We use plausibly good but imperfect definition sentences from Wikipedia as references to annotate sentences in a
Jiepu Jiang, James Allan 0001
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Distant Supervision For Chinese Semantic Role Labeling
2022 International Conference on Asian Language Processing (IALP), 2022Yi Zhang, Guirong Wang, Endong Xun
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