title: A Supervised Learning Approach to Acronym Identification
creator: Nadeau, David
creator: Turney, Peter
subject: Language
description: 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.
publisher: Springer
contributor: Kégl, Balázs
contributor: Lapalme, Guy
date: 2005
type: Conference Paper
type: PeerReviewed
format: application/pdf
identifier: http://cogprints.org/4399/1/NRC-48078.pdf
identifier:   Nadeau, David and Turney, Peter  (2005) A Supervised Learning Approach to Acronym Identification.  [Conference Paper]     
relation: http://cogprints.org/4399/