| Download | - View accepted manuscript: A Supervised Learning Approach to Acronym Identification (PDF, 290 KiB)
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| Author | Search for: Nadeau, D.; Search for: Turney, Peter1 |
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| Affiliation | - National Research Council Canada. NRC Institute for Information Technology
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| Format | Text, Article |
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| Conference | The Eighteenth Canadian Conference on Artificial Intelligence (AI'2005), May 9-11, 2005 |
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| 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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| Publication date | 2005 |
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| In | |
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| Language | English |
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| NRC number | NRCC 48121 |
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| NPARC number | 8913093 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 10d2325b-b18d-4ece-bbd3-9b1525b0443a |
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| Record created | 2009-04-22 |
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| Record modified | 2020-10-09 |
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