Automatic Acronym Dictionary Construction Based on Acronym Generation Types

Authors:
Yeo-Chan Yoon;So-Young Park;Young-In Song;Hae-Chang Rim;Dae-Woong Rhee
Affiliations:
-;-;-;-;-
Venue:
IEICE - Transactions on Information and Systems
Year:
2008

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Seeking Acronym Definitions: a Web-based Approach

Proceedings of the 2009 conference on Artificial Intelligence Research and Development: Proceedings of the 12th International Conference of the Catalan Association for Artificial Intelligence
Automatic extraction of acronym definitions from the Web

Applied Intelligence

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Abstract

In this paper, we propose a new model of automatically constructing an acronym dictionary. The proposed model generates possible acronym candidates from a definition, and then verifies each acronym-definition pair with a Naive Bayes classifier based on web documents. In order to achieve high dictionary quality, the proposed model utilizes the characteristics of acronym generation types: a syllable-based generation type, a word-based generation type, and a mixed generation type. Compared with a previous model recognizing an acronym-definition pair in a document, the proposed model verifying a pair in web documents improves approximately 50% recall on obtaining acronym-definition pairs from 314 Korean definitions. Also, the proposed model improves 7.25% F-measure on verifying acronym-definition candidate pairs by utilizing specialized classifiers with the characteristics of acronym generation types.