@inproceedings{pouran-ben-veyseh-etal-2021-maddog,
title = "{M}ad{D}og: A Web-based System for Acronym Identification and Disambiguation",
author = "Pouran Ben Veyseh, Amir and
Dernoncourt, Franck and
Chang, Walter and
Nguyen, Thien Huu",
editor = "Gkatzia, Dimitra and
Seddah, Djam{\'e}",
booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.eacl-demos.20",
doi = "10.18653/v1/2021.eacl-demos.20",
pages = "160--167",
abstract = "Acronyms and abbreviations are the short-form of longer phrases and they are ubiquitously employed in various types of writing. Despite their usefulness to save space in writing and reader{'}s time in reading, they also provide challenges for understanding the text especially if the acronym is not defined in the text or if it is used far from its definition in long texts. To alleviate this issue, there are considerable efforts both from the research community and software developers to build systems for identifying acronyms and finding their correct meanings in the text. However, none of the existing works provide a unified solution capable of processing acronyms in various domains and to be publicly available. 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. The web-based system is publicly available at \url{http://iq.cs.uoregon.edu:5000} and a demo video is available at \url{https://youtu.be/IkSh7LqI42M}. The system source code is also available at \url{https://github.com/amirveyseh/MadDog}.",
}
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<abstract>Acronyms and abbreviations are the short-form of longer phrases and they are ubiquitously employed in various types of writing. Despite their usefulness to save space in writing and reader’s time in reading, they also provide challenges for understanding the text especially if the acronym is not defined in the text or if it is used far from its definition in long texts. To alleviate this issue, there are considerable efforts both from the research community and software developers to build systems for identifying acronyms and finding their correct meanings in the text. However, none of the existing works provide a unified solution capable of processing acronyms in various domains and to be publicly available. 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. The web-based system is publicly available at http://iq.cs.uoregon.edu:5000 and a demo video is available at https://youtu.be/IkSh7LqI42M. The system source code is also available at https://github.com/amirveyseh/MadDog.</abstract>
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%0 Conference Proceedings
%T MadDog: A Web-based System for Acronym Identification and Disambiguation
%A Pouran Ben Veyseh, Amir
%A Dernoncourt, Franck
%A Chang, Walter
%A Nguyen, Thien Huu
%Y Gkatzia, Dimitra
%Y Seddah, Djamé
%S Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F pouran-ben-veyseh-etal-2021-maddog
%X Acronyms and abbreviations are the short-form of longer phrases and they are ubiquitously employed in various types of writing. Despite their usefulness to save space in writing and reader’s time in reading, they also provide challenges for understanding the text especially if the acronym is not defined in the text or if it is used far from its definition in long texts. To alleviate this issue, there are considerable efforts both from the research community and software developers to build systems for identifying acronyms and finding their correct meanings in the text. However, none of the existing works provide a unified solution capable of processing acronyms in various domains and to be publicly available. 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. The web-based system is publicly available at http://iq.cs.uoregon.edu:5000 and a demo video is available at https://youtu.be/IkSh7LqI42M. The system source code is also available at https://github.com/amirveyseh/MadDog.
%R 10.18653/v1/2021.eacl-demos.20
%U https://aclanthology.org/2021.eacl-demos.20
%U https://doi.org/10.18653/v1/2021.eacl-demos.20
%P 160-167
Markdown (Informal)
[MadDog: A Web-based System for Acronym Identification and Disambiguation](https://aclanthology.org/2021.eacl-demos.20) (Pouran Ben Veyseh et al., EACL 2021)
ACL
- Amir Pouran Ben Veyseh, Franck Dernoncourt, Walter Chang, and Thien Huu Nguyen. 2021. MadDog: A Web-based System for Acronym Identification and Disambiguation. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 160–167, Online. Association for Computational Linguistics.