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
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
