24 Hits in 3.2 sec

Cooperative Denoising for Distantly Supervised Relation Extraction

Kai Lei, Daoyuan Chen, Yaliang Li, Nan Du, Min Yang, Wei Fan, Ying Shen
2018 International Conference on Computational Linguistics  
Distantly supervised relation extraction greatly reduces human efforts in extracting relational facts from unstructured texts.  ...  Meanwhile, the useful information expressed in knowledge graph is still underutilized in the state-of-the-art methods for distantly supervised relation extraction.  ...  Acknowledgements We thank anonymous reviewers for their helpful comments.  ... 
dblp:conf/coling/LeiCLDY0S18 fatcat:e67x6ulty5c47nx67zots42hxe

Reinforcement Learning for Distantly Supervised Relation Extraction

Tingting Sun, Chunhong Zhang, Yang Ji, Zheng Hu
2019 IEEE Access  
In this paper, we propose a reinforcement learning-based label denoising method for distantly supervised relation extraction.  ...  The core of our label denoising is designing a policy in the PNet to obtain latent labels, where we can select the actions of using the distantly supervised labels or the predicted labels from the ENet  ...  In this paper, we creatively adopt RL to achieve label denoising for distantly supervised relation extraction.  ... 
doi:10.1109/access.2019.2930340 fatcat:zyqmuznt6bh7leonfld7v7hq2a

MSNet: Multi-head Self-attention Network for Distantly Supervised Relation Extraction

Tingting Sun, Chunhong Zhang, Yang Ji, Zheng Hu
2019 IEEE Access  
INDEX TERMS Relation extraction, distant supervision, multi-head self-attention, label denoising. 54472 2169-3536  ...  Distant supervision for relation extraction is a task of recognizing semantic relations between entities in a large amount of plain text weakly supervised by external knowledge bases, which can benefit  ...  CONCLUSION In this paper, we propose a MSNet based label denoising method for distantly supervised relation extraction.  ... 
doi:10.1109/access.2019.2913316 fatcat:qafranssy5epza7oqkkt7roteu

Adversarial Training for Weakly Supervised Event Detection

Xiaozhi Wang, Xu Han, Zhiyuan Liu, Maosong Sun, Peng Li
2019 Proceedings of the 2019 Conference of the North  
Modern weakly supervised methods for event detection (ED) avoid time-consuming human annotation and achieve promising results by learning from auto-labeled data.  ...  The experiments on two real-world datasets show that our candidate selection and adversarial training can cooperate together to obtain more diverse and accurate training data for ED, and significantly  ...  Distantly Supervised Scenarios The adaption for distantly supervised scenarios is similar to the adaption for semi-supervised scenarios.  ... 
doi:10.18653/v1/n19-1105 dblp:conf/naacl/WangHLSL19 fatcat:7rnaokme3rb5lgkjavvhn25rny

Adversarial training for supervised relation extraction

Yanhua Yu, Kanghao He, Jie Li
2022 Tsinghua Science and Technology  
Most supervised methods for relation extraction (RE) involve time-consuming human annotation.  ...  Distant supervision for RE is an efficient method to obtain large corpora that contains thousands of instances and various relations.  ...  Introduction Relation extraction (RE), which aims to extract relations between entity pairs from the sentences containing them, is of importance for many natural language applications, such as information  ... 
doi:10.26599/tst.2020.9010059 fatcat:sixt6gpxcfgzxnwatoha6nanry

A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios [article]

Michael A. Hedderich, Lukas Lange, Heike Adel, Jannik Strötgen, Dietrich Klakow
2021 arXiv   pre-print
This includes mechanisms to create additional labeled data like data augmentation and distant supervision as well as transfer learning settings that reduce the need for target supervision.  ...  A goal of our survey is to explain how these methods differ in their requirements as understanding them is essential for choosing a technique suited for a specific low-resource setting.  ...  models to distantly supervised relation extraction.  ... 
arXiv:2010.12309v3 fatcat:26dwmlkmn5auha2ob2qdlrvla4

AFET: Automatic Fine-Grained Entity Typing by Hierarchical Partial-Label Embedding

Xiang Ren, Wenqi He, Meng Qu, Lifu Huang, Heng Ji, Jiawei Han
2016 Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing  
Distant supervision has been widely used in current systems of fine-grained entity typing to automatically assign categories (entity types) to entity mentions.  ...  However, the types so obtained from knowledge bases are often incorrect for the entity mention's local context.  ...  Army Research Lab. under Cooperative Agreement No. W911NF-09-2-0053 (NSCTA), DARPA DEFT No.  ... 
doi:10.18653/v1/d16-1144 dblp:conf/emnlp/RenHQHJH16 fatcat:a3wionpxcbfmlhchxal6i2iitm

Phylogenetic farming: Can evolutionary history predict crop rotation via the soil microbiome?

Ian Kaplan, Nicholas A. Bokulich, J. Gregory Caporaso, Laramy S. Enders, Wadih Ghanem, Kathryn S. Ingerslew
2020 Evolutionary Applications  
yield, compared to more distantly related taxa  ...  For example, supervised learn- ing can be used to identify patterns in microbiome data that relate to different groups of samples (e.g., across experimental treatments or environmental gradients).  ... 
doi:10.1111/eva.12956 pmid:32908599 pmcid:PMC7463318 fatcat:dgj7mjvl4zfvbbilqoyzd5sjdq

Haemoprotozoan surveillance in peri-urban native and introduced wildlife from Australia

Siobhon L. Egan, Casey L. Taylor, Jill M. Austen, Peter B. Banks, Amy S. Northover, Liisa A. Ahlstrom, Una M. Ryan, Peter J. Irwin, Charlotte L. Oskam
2021 Current Research in Parasitology and Vector-Borne Diseases  
for more than one species.  ...  Molecular screening of DNA extracted from blood samples identified 52.2% (95% CI: 43.8-60.5%) of individuals were positive for at least one haemoprotozoan species, with 19.4% (95% CI: 13.4-26.7%) positive  ...  Christopher Peacock, for the provision of control isolates used for validation of assays.  ... 
doi:10.1016/j.crpvbd.2021.100052 pmid:35284862 pmcid:PMC8906138 fatcat:xrr76wwt5nc75gi53camnxngmq

A Survey on Knowledge Graphs: Representation, Acquisition and Applications [article]

Shaoxiong Ji and Shirui Pan and Erik Cambria and Pekka Marttinen and Philip S. Yu
2021 IEEE Transactions on Neural Networks and Learning Systems   accepted
For knowledge acquisition, especially knowledge graph completion, embedding methods, path inference, and logical rule reasoning, are reviewed.  ...  We further explore several emerging topics, including meta relational learning, commonsense reasoning, and temporal knowledge graphs.  ...  DSGAN [154] denoises distantly supervised relation extraction by learning a generator of sentence-level true positive samples and a discriminator that minimizes the probability of being true positive  ... 
doi:10.1109/tnnls.2021.3070843 pmid:33900922 arXiv:2002.00388v4 fatcat:4l2yxnf3wbg4zpzdumduvyr4he

Neural sequential transfer learning for relation extraction [article]

Christoph Benedikt Alt, Technische Universität Berlin, Sebastian Möller
I show how sequential transfer learning, specifically unsupervised language model pre-training, can improve performance and sample efficiency in supervised and distantly supervised relation extraction.  ...  Relation extraction (RE) is concerned with developing methods and models that automatically detect and retrieve relational information from unstructured data.  ...  distantly supervised relation extraction.  ... 
doi:10.14279/depositonce-11154 fatcat:qbkswybefnfzzod5nt3lcr4gny

MS-Ranker: Accumulating Evidence from Potentially Correct Candidates for Answer Selection [article]

Yingxue Zhang, Fandong Meng, Peng Li, Ping Jian, Jie Zhou
2020 arXiv   pre-print
this problem, we propose a novel reinforcement learning (RL) based multi-step ranking model, named MS-Ranker, which accumulates information from potentially correct candidate answers as extra evidence for  ...  Denoising distantly supervised open-domain question answering. In ACL. George A Miller. 1995. Wordnet: a lexical database for english. Communications of the ACM, 38(11):39–41.  ...  The one is the question-candidate attention (QC-attention), which is responsible for extract question-candidate matching information.  ... 
arXiv:2010.04970v1 fatcat:suedwlhvs5frpcaoqifhcaqgoy

Transfer Learning with Time Series Data: A Systematic Mapping Study

Manuel Weber, Maximilian Auch, Christoph Doblander, Peter Mandl, Hans-Arno Jacobsen
2021 IEEE Access  
for feature extraction.  ...  Without supervision, the authors train multiple stacked denoising autoencoders in the source domain. Each of these is then fine-tuned in the target domain.  ... 
doi:10.1109/access.2021.3134628 fatcat:66sxrp35bndjjeffxwy5jisa6q

The use of next generation sequencing for improving food safety: Translation into practice

Balamurugan Jagadeesan, Peter Gerner-Smidt, Marc W. Allard, Sébastien Leuillet, Anett Winkler, Yinghua Xiao, Samuel Chaffron, Jos Van Der Vossen, Silin Tang, Mitsuru Katase, Peter McClure, Bon Kimura (+3 others)
2019 Food microbiology  
Lieshout, Dr Belén Márquez-García and Dr Tobias Recker, Scientific Project Managers at ILSI Europe who facilitated scientific meetings and coordinated the overall project management and administrative tasks related  ...  Dag Harmsen, Dr Robèr Kempermann, Dr Trevor Phister and Dr Masami Takeuchi, for their contributions and suggestions when developing the publication.  ...  A distantly related reference genome can result in an underestimation of the genetic relatedness of the isolates being investigated as it increases the likelihood of mismapping and decreases the regions  ... 
doi:10.1016/ fatcat:letfnsihebdijczsan7rrkfwi4

Comparative Analysis of Different Machine Learning Classifiers for the Prediction of Chronic Diseases [chapter]

Rajesh Singh, Anita Gehlot, Dharam Buddhi
2022 Comparative Analysis of Different Machine Learning Classifiers for the Prediction of Chronic Diseases  
Precise diagnosis of these diseases on time is very significant for maintaining a healthy life.  ...  A comparative study of different machine learning classifiers for chronic disease prediction viz Heart Disease & Diabetes Disease is done in this paper.  ...  The Solar-Stirling engine systems can be the better option for off-grid power generation.  ... 
doi:10.13052/rp-9788770227667 fatcat:da47mjbbyzfwnbpde7rgbrlppe
« Previous Showing results 1 — 15 out of 24 results