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@misc{cogprints4399, volume = {LNCS 3}, editor = {Bal{\'a}zs K{\'e}gl and Guy Lapalme}, title = {A Supervised Learning Approach to Acronym Identification}, author = {David Nadeau and Peter Turney}, publisher = {Springer}, year = {2005}, pages = {319--329}, keywords = {acronym identification, supervised learning}, url = {http://cogprints.org/4399/}, abstract = {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.} }