Abstract
Domain dictionary is very useful in many Natural Language Processing (NLP) applications. This paper proposes a gloss-based word domain assignment algorithm to build domain dictionaries from machine-readable dictionary. Experiments on WordNet2.0 show that 62.53% of the first domain labels can match with the WordNet Domains3.0. Compared with the traditional corpus-based word domain assignment algorithms, this method can effectively use the existing dictionary resource and improve the accuracy of word domain assignment while reducing human efforts on corpus collection.
| Original language | English |
|---|---|
| Title of host publication | NLP-KE 2011 - Proceedings of the 7th International Conference on Natural Language Processing and Knowledge Engineering |
| Pages | 150-155 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2011 |
| Event | 7th International Conference on Natural Language Processing and Knowledge Engineering, NLP-KE 2011 - Tokushima, Japan Duration: 27 Nov 2011 → 29 Nov 2011 |
Publication series
| Name | NLP-KE 2011 - Proceedings of the 7th International Conference on Natural Language Processing and Knowledge Engineering |
|---|
Conference
| Conference | 7th International Conference on Natural Language Processing and Knowledge Engineering, NLP-KE 2011 |
|---|---|
| Country/Territory | Japan |
| City | Tokushima |
| Period | 27/11/11 → 29/11/11 |
Keywords
- Domain Assignment
- Electrical Dictionary
- NLP
- WordNet
- synset gloss
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Zhu, C., Shi, S., & Zhang, H. (2011). Gloss-based word domain assignment. In NLP-KE 2011 - Proceedings of the 7th International Conference on Natural Language Processing and Knowledge Engineering (pp. 150-155). Article 6138184 (NLP-KE 2011 - Proceedings of the 7th International Conference on Natural Language Processing and Knowledge Engineering). https://doi.org/10.1109/NLPKE.2011.6138184