  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.
