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Syntax-based Transfer Learning for the Task of Biomedical Relation Extraction

Joël Legrand, Yannick Toussaint, Chedy Raïssi, Adrien Coulet
2018 Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis  
In this paper, we experiment with TL for the task of Relation Extraction (RE) from biomedical texts, using the TreeLSTM model.  ...  Transfer learning (TL) proposes to enhance machine learning performance on a problem, by reusing labeled data originally designed for a related problem.  ...  Figure 4 : 4 Dependency parse tree of a sentence from SNPPhena expressing a relation between the entities rs429358 and dementia.  ... 
doi:10.18653/v1/w18-5617 dblp:conf/acl-louhi/LegrandTRC18 fatcat:darkxdyi3jfxtfdapuxe2hhlta

Syntax-based transfer learning for the task of biomedical relation extraction

Joël Legrand, Yannick Toussaint, Chedy Raïssi, Adrien Coulet
2021 Journal of Biomedical Semantics  
Results In this paper, we experiment with transfer learning for the task of relation extraction from biomedical texts, using the TreeLSTM model.  ...  Conclusion Given the difficulty to manually annotate corpora in the biomedical domain, the proposed transfer learning method offers a promising alternative to achieve good relation extraction performances  ...  Fig. 4 4 Fig. 4 Dependency parse tree of a sentence from SNPPhena expressing a relation between the entities rs429358 and dementia.  ... 
doi:10.1186/s13326-021-00248-y pmid:34407869 pmcid:PMC8371836 fatcat:kgyy6qgydbhprl26pjnd2launu

Tree Kernel-based Protein-Protein Interaction Extraction Considering both Modal Verb Phrases and Appositive Dependency Features

Changlin Ma, Yong Zhang, Maoyuan Zhang
2015 Proceedings of the 24th International Conference on World Wide Web - WWW '15 Companion  
The experimental results show that the new method achieves better results on five commonly used corpora.  ...  In order to resolve the parsing error resulted from modal verb phrases and the noise interference brought by appositive dependency, an improved tree kernel-based PPI extraction method is proposed in this  ...  The Stanford parser is used to generate CPT and SD CCprocessed dependency relation tuples for sentences in the above corpora. Qian et al.  ... 
doi:10.1145/2740908.2741705 dblp:conf/www/MaZZ15 fatcat:z4c5vsgln5hrlfmoqkip627j54

PKDE4J: Entity and relation extraction for public knowledge discovery

Min Song, Won Chul Kim, Dahee Lee, Go Eun Heo, Keun Young Kang
2015 Journal of Biomedical Informatics  
We demonstrate its competitive performance by evaluating it on many corpora and found that it surpasses existing systems with average F-measures of 85% for entity extraction and 81% for relation extraction  ...  Due to an enormous number of scientific publications that cannot be handled manually, there is a rising interest in text-mining techniques for automated information extraction, especially in the biomedical  ...  After pre-processing, we traverse the resulting dependency tree to find relation triplets by using a predefined set of relation rules for a dependency tree.  ... 
doi:10.1016/j.jbi.2015.08.008 pmid:26277115 fatcat:sfgmji7zu5efbbo6xyarry7h4e

Dependency-Driven Feature-based Learning for Extracting Protein-Protein Interactions from Biomedical Text

Bing Liu, Longhua Qian, Hongling Wang, Guodong Zhou
2010 International Conference on Computational Linguistics  
This paper incorporates dependency information as well as other lexical and syntactic knowledge in a feature-based framework.  ...  Additionally, we explore the difference of lexical characteristics between biomedical and newswire domains.  ...  Antti Airola from Truku University for providing partial experimental materials.  ... 
dblp:conf/coling/LiuQWZ10 fatcat:7g7poejuy5an5c3eri2bq6xule

Bridging semantics and syntax with graph algorithms—state-of-the-art of extracting biomedical relations

Yuan Luo, Özlem Uzuner, Peter Szolovits
2016 Briefings in Bioinformatics  
Research on extracting biomedical relations has received growing attention recently, with numerous biological and clinical applications including those in pharmacogenomics, clinical trial screening and  ...  However, a number of problems at the frontiers of biomedical relation extraction continue to pose interesting challenges and present opportunities for great improvement and fruitful research.  ...  Acknowledgement The work was supported in part by Grant Number U54LM008748 from the National Library of Medicine, NIH 154HG007963 from the National Human Genome Research Institute and by the Scullen Center  ... 
doi:10.1093/bib/bbw001 pmid:26851224 pmcid:PMC5221425 fatcat:z6sptxngubempdx6kthsyab7be

High-Precision Biomedical Relation Extraction for Reducing Human Curation Efforts in Industrial Applications

Alan Ramponi, Stefano Giampiccolo, Danilo Tomasoni, Corrado Priami, Rosario Lombardo
2020 IEEE Access  
This growth has created interest in biomedical relation extraction approaches to extract domain-specific knowledge for diverse applications.  ...  The body of biomedical literature is growing at an unprecedented rate, exceeding the ability of researchers to make effective use of this knowledge-rich amount of information.  ...  Other kernelbased approaches for biomedical relation extraction include a linguistic pattern-aware dependency tree kernel combined with a tree kernel [24] , a convolution tree kernel [25] , and a distributed  ... 
doi:10.1109/access.2020.3014862 fatcat:xhuubcxshjgvxmkjftwheivsz4

Tree kernel-based protein–protein interaction extraction from biomedical literature

Longhua Qian, Guodong Zhou
2012 Journal of Biomedical Informatics  
Compared with previously used constituent tree setups, our dependency-motivated constituent tree setup achieves the best results across five commonly used PPI corpora.  ...  In this paper, we propose a novel approach to tree kernel-based PPI extraction, where the tree representation generated from a constituent syntactic parser is further refined using the shortest dependency  ...  Bunescu and Mooney [6] adopt a generalized substring kernel over a mixture of words and word classes to extract protein interactions from biomedical corpora as well as semantic relations from newswire  ... 
doi:10.1016/j.jbi.2012.02.004 pmid:22388011 fatcat:lo4npz4ic5a4blciur3hfqavv4

A fast and effective dependency graph kernel for PPI relation extraction

Domonkos Tikk, Peter Palaga, Ulf Leser
2010 BMC Bioinformatics  
BMC Bioinformatics 2010, 11(Suppl 5):P8 using document-level 10-fold cross-validation (CV) and cross-learning (CL; 4-vs-1) evaluation.  ...  Kernel functions differ in (1) the underlying sentence representation (bag-of-words, syntax tree parse, dependency graphs), (2) the substructures retrieved from the sentence representation to define interactions  ...  Kernel functions differ in (1) the underlying sentence representation (bag-of-words, syntax tree parse, dependency graphs), (2) the substructures retrieved from the sentence representation to define interactions  ... 
doi:10.1186/1471-2105-11-s5-p8 pmcid:PMC2956401 fatcat:gvsxsx4c2jhftlepypppubimme

Biomedical Relation Extraction: From Binary to Complex

Deyu Zhou, Dayou Zhong, Yulan He
2014 Computational and Mathematical Methods in Medicine  
Biomedical relation extraction aims to uncover high-quality relations from life science literature with high accuracy and efficiency.  ...  In the paper, we conduct a thorough survey on the research in biomedical relation extraction.  ...  [24] used PATRICIA trees for learning PPI extraction patterns. All training sentences are inserted and stored in a generic PATRICIA tree.  ... 
doi:10.1155/2014/298473 pmid:25214883 pmcid:PMC4156999 fatcat:2vxivwh3zjgmdioqyet7g4enfq

Combining Tree Structures, Flat Features and Patterns for Biomedical Relation Extraction

Md. Faisal Mahbub Chowdhury, Alberto Lavelli
2012 Conference of the European Chapter of the Association for Computational Linguistics  
This also demonstrates that the different types of information that we use are able to complement each other for relation extraction.  ...  In this paper, we propose a novel hybrid kernel that combines (automatically collected) dependency patterns, trigger words, negative cues, walk features and regular expression patterns along with tree  ...  The authors are grateful to Alessandro Moschitti for his help in the use of SVM-LIGHT-TK. We also thank the anonymous reviewers for helpful suggestions.  ... 
dblp:conf/eacl/ChowdhuryL12 fatcat:3ud3ylp6a5dsbiwkwvkuea66n4

Bridging semantics and syntax with graph algorithms—state-of-the-art of extracting biomedical relations

Yuan Luo, Özlem Uzuner, Peter Szolovits
2017 Briefings in Bioinformatics  
To make better use of existing annotated corpora, it is necessary to perform domain adaptation from external training corpora (source) to the target corpora.  ...  Applying this method on learning from seven event annotated corpora, they showed improved performance on two tasks in BioNLP-ST-2011.  ...  [125] Stanford Grammatical rules to traverse the tree structures Yes HIVDB [154] , Re-gaDB [155] Pre-specified drug names and regular expressions Katrenko et al.  ... 
doi:10.1093/bib/bbx048 pmid:28472242 pmcid:PMC6080366 fatcat:3pu74myraffsnjttvnlgoy6kqq

Using Neural Networks for Relation Extraction from Biomedical Literature [article]

Diana Sousa, Andre Lamurias, Francisco M. Couto
2019 arXiv   pre-print
Several relation extraction approaches have been proposed to identify relations between concepts in biomedical literature, namely using neural networks algorithms.  ...  Using different sources of information to support automated extracting of relations between biomedical concepts contributes to the development of our understanding of biological systems.  ...  -Machine Learning (ML)-based: usually makes use of large annotated biomedical corpora (supervised learning) to perform RE.  ... 
arXiv:1905.11391v1 fatcat:uw2nifl7ufamfifi2kx3bx7yey

A Short Survey of Biomedical Relation Extraction Techniques [article]

Elham Shahab
2017 arXiv   pre-print
Biomedical information is growing rapidly in the recent years and retrieving useful data through information extraction system is getting more attention.  ...  In the current research, we focus on different aspects of relation extraction techniques in biomedical domain and briefly describe the state-of-the-art for relation extraction between a variety of biological  ...  dependency parse trees.  ... 
arXiv:1707.05850v3 fatcat:snyvtomcxbbeplkspqaucmpely

Protein-Protein Interaction Extraction using Attention-based Tree-Structured Neural Network Models

Sudipta Singha Roy, Robert E. Mercer
2022 Proceedings of the ... International Florida Artificial Intelligence Research Society Conference  
Unlike sequential models, tree-structured neural network models have the ability to consider syntactic and semantic dependencies between different portions of the text and can provide structural information  ...  It is typically quite difficult to extract a protein-protein interaction (PPI) from text data as text data is complex in nature.  ...  For the evaluation of these models, we used 10-fold cross validation using StratifiedK-Fold from the scikit-learn package. Both of the tree-LSTM models are initialized with learning rate 0.1.  ... 
doi:10.32473/flairs.v35i.130660 fatcat:3jc22eraxzbaxb5qofaqus5w7m
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