Automatic Acronym Dictionary Construction Based on Acronym Generation Types

Yeo-Chan YOON  So-Young PARK  Young-In SONG  Hae-Chang RIM  Dae-Woong RHEE  

IEICE TRANSACTIONS on Information and Systems   Vol.E91-D   No.5   pp.1584-1587
Publication Date: 2008/05/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e91-d.5.1584
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Natural Language Processing
acronym,  automatic dictionary construction,  

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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.