Statistical Model for Japanese Abbreviations

Authors:
Norifumi Murayama;Manabu Okumura
Affiliations:
Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology,;Precision and Intelligence Laboratory, Tokyo Institute of Technology,
Venue:
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Year:
2008

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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.