%A David Nadeau
%A Peter Turney
%T A Supervised Learning Approach to Acronym Identification
%X This paper addresses the task of finding acronym-definition pairs in text. Most of the previous work on the topic is about systems that involve manually generated rules or regular expressions. In this paper, we present a
supervised learning approach to the acronym identification task. Our approach reduces the search space of the supervised learning system by putting some weak constraints on the kinds of acronym-definition pairs that can be identified. We obtain results comparable to hand-crafted systems that use stronger constraints. We describe our method for reducing the search space, the features
used by our supervised learning system, and our experiments with various learning schemes.
%K acronym identification, supervised learning
%P 319-329
%E Bal?zs K?gl
%E Guy Lapalme
%V LNCS 3
%D 2005
%I Springer
%L cogprints4399

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