Abstract
A process that attempts to solve abbreviation ambiguity is presented. Various context-related features and statistical features have been explored. Almost all features are domain independent and language independent. The application domain is Jewish Law documents written in Hebrew. Such documents are known to be rich in ambiguous abbreviations. Various implementations of the one sense per discourse hypothesis are used, improving the features with new variants. An accuracy of 96.09% has been achieved by SVM.
| Original language | English |
|---|---|
| Pages (from-to) | 61-64 |
| Number of pages | 4 |
| Journal | Proceedings of the Annual Meeting of the Association for Computational Linguistics |
| State | Published - 2008 |
| Externally published | Yes |
| Event | 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL 2008 - Columbus, United States Duration: 16 Jun 2008 → 17 Jun 2008 |
Bibliographical note
Publisher Copyright:© 2008 Association for Computational Linguistics.