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%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