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Investigation of unsupervised pattern learning techniques for bootstrap construction of a medical treatment lexicon
2009
Proceedings of the Workshop on BioNLP - BioNLP '09
unpublished
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Focusing on medical treatment concepts (e.g. drugs, medical procedures and medical devices), we have developed an unsupervised, iterative pattern learning approach for constructing a comprehensive dictionary ...
We have investigated different methods of seeding, either with a seed pattern or seed instances (terms), and have compared different ranking methods for ranking extracted context patterns and instances ...
Acknowledgments RX is supported by NLM training grant LM007033 and Stanford Medical School. ...
doi:10.3115/1572364.1572373
fatcat:tpv3cxpgujgmhkvuvmqjfdcctm
Machine learning in medicine: a practical introduction to natural language processing
2021
BMC Medical Research Methodology
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Background Unstructured text, including medical records, patient feedback, and social media comments, can be a rich source of data for clinical research. ...
The purpose of this paper is to provide a practical introduction to contemporary techniques for the analysis of text-data, using freely-available software. ...
Acknowledgements We would like to acknowledge and thank contributors to the University of California, Irvine Machine Learning Repository who have made large datasets available for public use. ...
doi:10.1186/s12874-021-01347-1
fatcat:s7a2h7qdird7tfs4rdjgwpyvyu
Improved Pattern Learning for Bootstrapped Entity Extraction
2014
Proceedings of the Eighteenth Conference on Computational Natural Language Learning
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Bootstrapped pattern learning for entity extraction usually starts with seed entities and iteratively learns patterns and entities from unlabeled text. ...
Our system outperforms existing pattern scoring algorithms for extracting drug-andtreatment entities from four medical forums. ...
Acknowledgments We thank Diana MacLean for labeling the test data for calculating the inter-annotator agreement. ...
doi:10.3115/v1/w14-1611
dblp:conf/conll/GuptaM14
fatcat:4q5yngztdjhzzeh3ct544bfycq
Data-Driven Information Extraction from Chinese Electronic Medical Records
2015
PLoS ONE
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It consists of constructing cross-domain core medical lexica, an unsupervised, iterative algorithm to accrue more accurate terms into the lexica, rules to address Chinese writing conventions and temporal ...
Discussion In terms of named entity recognition, the proposed framework outperforms state-of-the-art supervised learning algorithms (F1-score: 0.896 vs. 0.886). ...
We used an unsupervised iterative process to bootstrap the existing lexica based on learned patterns. ...
doi:10.1371/journal.pone.0136270
pmid:26295801
pmcid:PMC4546596
fatcat:p4pgwqmazne5jbheoghviojkrm
Learning for Biomedical Information Extraction: Methodological Review of Recent Advances
[article]
2016
arXiv
pre-print
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In addition, we dive into open information extraction and deep learning, two emerging and influential techniques and envision next generation of BioIE. ...
Unlike existing reviews covering a holistic view on BioIE, this review focuses on mainly recent advances in learning based approaches, by systematically summarizing them into different aspects of methodological ...
Deep Learning Deep learning refers to "a class of machine learning techniques that exploit many layers of non-linear information processing for supervised or unsupervised feature extraction and transformation ...
arXiv:1606.07993v1
fatcat:7d5om7zxxzhoviiriasrfwg3xi
Automatic generation of lexica for sentiment polarity shifters
2020
Natural Language Engineering
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Instead, we develop a bootstrapping approach that combines automatic classification with human verification to ensure the high quality of our lexicon while reducing annotation costs by over 70%. ...
Our approach leverages a number of linguistic insights; while some features are based on textual patterns, others use semantic resources or syntactic relatedness. ...
We would like to thank Amy Isard for her invaluable feedback during the writing and revision of this article. We would also like to thank the anonymous reviewers for their constructive comments. ...
doi:10.1017/s135132492000039x
fatcat:jauqzbifwnfpteeykcuzpio2py
Identifying References to Datasets in Publications
[chapter]
2012
Lecture Notes in Computer Science
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To overcome the sparse distribution of training instances, we induce patterns iteratively using a bootstrapping approach. ...
In this paper, we propose a pattern induction method for the detection of study references in full texts. ...
This work is funded by the DFG as part of the InFoLiS project (SU 647/2-1). We would like to thank Benjamin Zapilko and Christian Meilicke for their great support. ...
doi:10.1007/978-3-642-33290-6_17
fatcat:r47kifnyivdjfeefau2lx3hfya
A Variational Approach to Unsupervised Sentiment Analysis
[article]
2020
arXiv
pre-print
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We can learn a sentiment classifier by optimizing the lower bound. ...
In this paper, we propose a variational approach to unsupervised sentiment analysis. ...
., 2011) identified dependency paths that link opinion words and targets via a bootstrapping process. This method only needs an initial opinion lexicon to start the bootstrapping process. ...
arXiv:2008.09394v1
fatcat:kmxpov65sbeizen3gtsojs5djm
Self-Supervised Euphemism Detection and Identification for Content Moderation
[article]
2021
arXiv
pre-print
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Our algorithm for revealing euphemistic meanings of words is the first of its kind, as far as we are aware. ...
Compared to the existing state of the art, which uses context-free word embeddings, our algorithm for detecting euphemisms achieves 30-400% higher detection accuracies of unlabeled euphemisms in a text ...
It lists a set of euphemism candidates using a bootstrapping algorithm for semantic lexicon induction. ...
arXiv:2103.16808v1
fatcat:z44viumb25bxdmdyr66gfoxipu
Without lexicons, multiword expression identification will never fly: A position statement
2019
Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019)
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We define requirements for such a minimal NLP-oriented lexicon, and we propose a roadmap for the MWE community driven by these requirements. ...
Such lexicons need not necessarily achieve a linguistically complete modelling of MWEs' behavior, but they should provide minimal morphosyntactic information to cover some potential uses, so as to complement ...
Acknowledgments This work was funded by the French PARSEME-FR project (ANR-14-CERA-0001). 15 We are grateful to Jakub Waszczuk and Kilian Evang for their valuable feedback at an early stage of our proposal ...
doi:10.18653/v1/w19-5110
dblp:conf/mwe/SavaryCR19
fatcat:d5rovrbxhnapno7ncnon45noay
Relation Extraction for Open and Closed Domain Question Answering
[chapter]
2011
Interactive Multi-modal Question-Answering
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We show that dependency patterns enriched with semantic concept labels give accurate results for relations that are relevant for a medical question answering system. ...
In this chapter, we present two methods for learning relation instances for relations relevant in a closed and open domain (medical) question answering system. ...
Inspired by the good results of this system in the TREC 2001 evaluation, Ravichandran and Hovy (2002) , Fleischman et al (2003) and others investigated techniques for learning such extraction patterns ...
doi:10.1007/978-3-642-17525-1_8
dblp:series/tanlp/BoumaFM11
fatcat:jkoly4jsljaxfgfky3xs547j3i
A Review of Knowledge Graph-based Question and Answer System Research and Its Application in Chronic Disease Diagnosis
2021
Academic Journal of Computing & Information Science
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The question and answer system can be divided into three parts: question classification, entity recognition, and relationship extraction, for each of which a large number of techniques have been studied ...
Finally, a question and answer system based on the knowledge graph of chronic diseases is designed to provide a proven solution for this field, in view of the problem that there are many patients with ...
Semi-supervised learning is based on a small number of artificially added entity pair seeds and a large number of unlabeled samples, using pattern learning methods for iterative training to obtain a classification ...
doi:10.25236/ajcis.2021.040401
fatcat:x4nnh274wjbxpgxhfbhzx77cny
Semantic annotation for knowledge management: Requirements and a survey of the state of the art
2006
Journal of Web Semantics
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While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. ...
In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. ...
Acknowledgements This work was funded by the Advanced Knowledge Technologies (AKT) Interdisciplinary Research Collaboration (IRC), the Designing Adaptive Information Extraction for Knowledge Management ...
doi:10.1016/j.websem.2005.10.002
fatcat:r2bm35nnifdcbibp2phnvyuo4e
Semantic Annotation for Knowledge Management: Requirements and a Survey of the State of the Art
2006
Social Science Research Network
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While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. ...
In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. ...
Acknowledgements This work was funded by the Advanced Knowledge Technologies (AKT) Interdisciplinary Research Collaboration (IRC), the Designing Adaptive Information Extraction for Knowledge Management ...
doi:10.2139/ssrn.3199324
fatcat:s4kabxi2tzhr5hywjoruu3jpt4
Message from the general chair
2015
2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
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Joint Learning for Coreference Resolution with Markov Logic
Resolving "This-issue" Anaphora Varada Kolhatkar and Graeme Hirst Saturday 12:00pm-12:30pm -202 A (ICC) We annotate and resolve a particular ...
To maximize the utility of the injected knowledge, we deploy a learning-based multi-sieve approach and develop novel entity-based features. ...
Glossaries for several domains are iteratively acquired from the Web by means of a bootstrapping technique. ...
doi:10.1109/ispass.2015.7095776
dblp:conf/ispass/Lee15
fatcat:ehbed6nl6barfgs6pzwcvwxria
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