@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.}
}

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