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Acronym Disambiguation Using Word Embedding

Chao Li, Lei Ji, Jun Yan
2015 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
In this paper, we propose two word embedding based models for acronym disambiguation.  ...  The experimental results show that word embedding helps to improve acronym disambiguation.  ...  So it is important to disambiguate these acronyms. Acronym disambiguation is a subset of the more general problem of Word Sense Disambiguation (WSD), which is to decide the sense of words in context.  ... 
doi:10.1609/aaai.v29i1.9713 fatcat:mm67zylfurhednqzqg7t7fia6i

Using Word Embeddings for Unsupervised Acronym Disambiguation

Jean Charbonnier, Christian Wartena, International Committee On Computational Linguistics (ICCL)
2018
We learn word embeddings for all words in the corpus and compare the averaged context vector of the words in the expansion of an acronym with the weighted average vector of the words in the context of  ...  Furthermore, we show that word embeddings learned from a 1 billion word corpus of scientific exts outperform word embeddings learned from much larger general corpora.  ...  evaluated the effect of domain specific corpora for disambiguating medical terms while using word embeddings.  ... 
doi:10.25968/opus-1265 fatcat:suiuzm63mnckpk4t4qcnonfjmy

Disambiguation of Biomedical Acronyms Based on a Bidirectional Recurrent Neural Network of Character-level Features

Ren Κai, College of Computer Science, South-Central University for Nationalities, Wuhan, China, Li Na, Xiong Wei, Wang Shi-Wen, College of Computer Science, South-Central University for Nationalities, Wuhan, China, College of Computer Science, South-Central University for Nationalities, Wuhan, China, Sociologue, Université Toulouse-Jean-Jaurès, Toulouse, France
2019 Journal of Engineering Science and Technology Review  
To address the disambiguation of acronyms in the biomedical domain, most associated studies are based on methods using word-level contextual features.  ...  The results of acronym disambiguation based on character-level feature model were also compared with those based on word-level feature models.  ...  The character-level model uses no word embedding form. The word embedding model in the control word-level model generated 200D word vector for training the Bi-LSTM model.  ... 
doi:10.25103/jestr.126.13 fatcat:6va4aj3qqrbuzn7m2xljklti44

Participation of UC3M in SDU@AAAI-21: A Hybrid Approach to Disambiguate Scientific Acronyms

Areej Jaber, Paloma Martínez
2021 AAAI Conference on Artificial Intelligence  
Acronyms disambiguation is considered a word sense disambiguation (WSD) task which consists on determining the correct expansion of an acronym based on a given context.  ...  This paper describes three hybrid systems to disambiguate acronyms in scientific documents, which combine three supervised machine learning (ML) models (Support Vector Machine, Naive Bayes and K-Nearest  ...  Pre-trained word embedding features: A pre-trained word embedding model with 300 dimension vectors was built used FastText (Joulin et al. 2016 ) generated from several English resources such as the Wikipedia  ... 
dblp:conf/aaai/JaberM21 fatcat:riv5ctkqovhfdl2zgeowhnmaki

Acronym Disambiguation in Clinical Notes from Electronic Health Records [article]

Nicholas Byron Link, Sicong Huang, Tianrun Cai, Zeling He, Jiehuan Sun, Kumar Dahal, Lauren Costa, Kelly Cho, Katherine Liao, Tianxi Cai, Chuan Hong
2020 medRxiv   pre-print
Conclusion: CASEml is a novel method that accurately disambiguates acronyms in clinical notes and has advantages over commonly used supervised and unsupervised machine learning approaches.  ...  In this study we introduce an unsupervised method for acronym disambiguation, the task of classifying the correct sense of acronyms in the clinical EHR notes.  ...  Word embeddings and à la carte As reported in previous work [25 27 ], the unsupervised (or semi-supervised) word embeddings approach using sense expansions accurately disambiguated acronyms.  ... 
doi:10.1101/2020.11.25.20221648 fatcat:vrjo7s3rezdijeec6hamkkzg4a

Acronym Disambiguation: A Domain Independent Approach [article]

Aditya Thakker, Suhail Barot, Sudhir Bagul
2017 arXiv   pre-print
We propose to use these expansions to collect all possible contexts in which these acronyms are used and then score them using a paragraph embedding technique called Doc2Vec.  ...  In this paper, we propose a general system for acronym disambiguation that can work on any acronym given some context information.  ...  to the acronym disambiguation problem.  ... 
arXiv:1711.09271v3 fatcat:22pwub5twfabnkpkc367whsf2i

Acronym Expander at SDU@AAAI-21: an Acronym Disambiguation Module

João L. M. Pereira, Helena Galhardas, Dennis Shasha
2021 AAAI Conference on Artificial Intelligence  
This paper describes the techniques we use for that problem for the SDU@AAAI benchmark in which context was provided in the form of sentences in which acronym A is present and defined.  ...  In order to properly determine which of several possible meanings an acronym A in sentence s has, any system that aims to find the correct meaning for A must understand the context of s.  ...  Classic Context Vector The context vector technique is an unsupervised method used as a baseline in Word Sense Disambiguation problems (Abdalgader and Skabar 2012) and also in acronym disambiguation  ... 
dblp:conf/aaai/PereiraGS21 fatcat:4qso3ag7bbakncsv2ciifjrgpa

What Does This Acronym Mean? Introducing a New Dataset for Acronym Identification and Disambiguation [article]

Amir Pouran Ben Veyseh, Franck Dernoncourt, Quan Hung Tran, Thien Huu Nguyen
2020 arXiv   pre-print
Due to their importance, identifying acronyms and corresponding phrases (i.e., acronym identification (AI)) and finding the correct meaning of each acronym (i.e., acronym disambiguation (AD)) are crucial  ...  More specifically, limited size of manually annotated AI datasets or noises in the automatically created acronym identification datasets obstruct designing advanced high-performing acronym identification  ...  Sentence Encoder We represent the word w i of W using its corresponding pre-trained word embedding.  ... 
arXiv:2010.14678v1 fatcat:pwatnxkfunb43bm34t73rjfyvu

BERT-based Acronym Disambiguation with Multiple Training Strategies [article]

Chunguang Pan, Bingyan Song, Shengguang Wang, Zhipeng Luo
2021 arXiv   pre-print
Although it is convenient to use acronyms, sometimes they could be difficult to understand. Identifying the appropriate expansions of an acronym is a practical task in natural language processing.  ...  Acronym disambiguation (AD) task aims to find the correct expansions of an ambiguous ancronym in a given sentence.  ...  These learned encoders are still needed to generate word embeddings in context when being used in downstream tasks.  ... 
arXiv:2103.00488v2 fatcat:rnllmywavjbl5onjhhxgejdm54

Leveraging Domain Agnostic and Specific Knowledge for Acronym Disambiguation

Qiwei Zhong, Guanxiong Zeng, Danqing Zhu, Yang Zhang, Wangli Lin, Ben Chen, Jiayu Tang
2021 AAAI Conference on Artificial Intelligence  
Acronym disambiguation aims to find the correct meaning of an ambiguous acronym in a given text.  ...  Recent efforts attempted to incorporate word embeddings and deep learning architectures, and achieved significant effects in this task.  ...  Acknowledgments We thank the organizers of acronym identification and disambiguation competitions and the reviewers for their valuable comments and suggestions.  ... 
dblp:conf/aaai/ZhongZZZLCT21 fatcat:ma47e3sszvasjcfchsy7l4xlge

Leveraging Domain Agnostic and Specific Knowledge for Acronym Disambiguation [article]

Qiwei Zhong, Guanxiong Zeng, Danqing Zhu, Yang Zhang, Wangli Lin, Ben Chen, Jiayu Tang
2021 arXiv   pre-print
Acronym disambiguation aims to find the correct meaning of an ambiguous acronym in a given text.  ...  Recent efforts attempted to incorporate word embeddings and deep learning architectures, and achieved significant effects in this task.  ...  Acknowledgments We thank the organizers of acronym identification and disambiguation competitions and the reviewers for their valuable comments and suggestions.  ... 
arXiv:2107.00316v1 fatcat:vozjxkipjzecnnpnwmbekctpby

Acronym Disambiguation using Web Scraping

2020 International Journal of Engineering and Advanced Technology  
In this paper, an acronym disambiguation system is built by web scraping using Jsoup and cosine similarity score is used to identify the most suitable acronym.  ...  Acronym disambiguation is mainly used in chat bot, named entity recognition, natural language processing and so on.  ...  To find the cosine similarity, initially context files should be converted in a word2vec format to create the word embedding. Word embedding [11] is most used representation for documents.  ... 
doi:10.35940/ijeat.d6812.049420 fatcat:cjgi2wjd5rarve63k7z5q6zyiq

Primer AI's Systems for Acronym Identification and Disambiguation [article]

Nicholas Egan, John Bohannon
2021 arXiv   pre-print
We introduce new methods for acronym identification and disambiguation: our acronym identification model projects learned token embeddings onto tag predictions, and our acronym disambiguation model finds  ...  The prevalence of ambiguous acronyms make scientific documents harder to understand for humans and machines alike, presenting a need for models that can automatically identify acronyms in text and disambiguate  ...  Our acronym identification model uses a transformer followed by linear projection, and our acronym disambiguation model finds similar examples with embeddings learned from Twin Networks.  ... 
arXiv:2012.08013v2 fatcat:kcsskg4pv5adhfx7ilvwhakgmu

MadDog: A Web-based System for Acronym Identification and Disambiguation [article]

Amir Pouran Ben Veyseh, Franck Dernoncourt, Walter Chang, Thien Huu Nguyen
2021 arXiv   pre-print
Thus, we provide the first web-based acronym identification and disambiguation system which can process acronyms from various domains including scientific, biomedical, and general domains.  ...  used far from its definition in long texts.  ...  . , w n ] with the ambiguous acronym w a , we first represent each word using the corresponding GloVe embedding, i.e., X = [x 1 , x 2 , . . . , x n ].  ... 
arXiv:2101.09893v1 fatcat:5saqrbvgizflvnsbbqryl5ihie

SciDr at SDU-2020: IDEAS – Identifying and Disambiguating Everyday Acronyms for Scientific Domain [article]

Aadarsh Singh, Priyanshu Kumar
2021 arXiv   pre-print
We present our systems submitted for the shared tasks of Acronym Identification (AI) and Acronym Disambiguation (AD) held under Workshop on SDU. We mainly experiment with BERT and SciBERT.  ...  For AD, we formulate the problem as a span prediction task, experiment with different training techniques and also leverage the use of external data.  ...  Jin, Liu, and Lu (2019) explore the usage of contextualised BioELMO word embeddings for acronym disambiguation.  ... 
arXiv:2102.08818v2 fatcat:flemuuficjai3iokwkjhhhnn2i
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