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Issue title: Artificial Intelligence
Guest editors: Tu Bao Hox, Zhi-Hua Zhouy and Hiroshi Motodaz
Article type: Research Article
Authors: Murayama, Norifumia; * | Okumura, Manabub
Affiliations: [a] Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology, Tokyo, Japan | [b] Precision and Intelligence Laboratory, Tokyo Institute of Technology, Tokyo, Japan | [x] Japan Advanced Institute of Science and Technology, Ishikawa, Japan | [y] Nanjing University, Nanjing, China | [z] Osaka University and AFOSR/AOARD, Osaka, Japan
Correspondence: [*] Corresponding author: Norifumi Murayama, E-mail: murayam@blogwatcher.co.jp.
Abstract: We present a new approach to detect abbreviations given a root expression. The method is based on a statistical model combining two internal models: a generation and a verification model. The statistical model accounts for both the validity of abbreviations as a character sequence generated from a root (as learnt from the collection of abbreviation-root pairs) and their social validity, indicating how they are really used in the world (as obtained from a web search engine). The experimental results showed that our method outperforms traditional template-based methods. Specifically, using co-occurrence in the verification model yielded the best performance in our method.
Keywords: Japanese abbreviation, statistical model, generation model
DOI: 10.3233/IDA-2010-0432
Journal: Intelligent Data Analysis, vol. 14, no. 4, pp. 465-478, 2010
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