As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Acronyms are widely used in many domains to abbreviate and stress important concepts. Due to its dynamicity and unbounded nature, manual attempts to compose a global scale repository of acronym-definition pairs result in an overwhelming amount of work and limited amount of results. Attending these shortcomings, the paper presents an automatic and non-supervised methodology to generate acronyms and extract their possible definitions from the Web. The method has been designed in order to minimize the set of constraints, offering a domain and -partially- language independent solution. The obtained results have been manually evaluated against the largest manually built acronym repository (Acronym Finder). The results obtained after this comparison show that the proposed automatic web-based approach is able to improve the coverage of manual attempts offering a high precision.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.