@inproceedings{966c501b7c284c41b89b2911f5d03304,
title = "Gloss-based word domain assignment",
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.",
keywords = "Domain Assignment, Electrical Dictionary, NLP, WordNet, synset gloss",
author = "Chaoyong Zhu and Shumin Shi and Haijun Zhang",
year = "2011",
doi = "10.1109/NLPKE.2011.6138184",
language = "English",
isbn = "9781612847283",
series = "NLP-KE 2011 - Proceedings of the 7th International Conference on Natural Language Processing and Knowledge Engineering",
pages = "150--155",
booktitle = "NLP-KE 2011 - Proceedings of the 7th International Conference on Natural Language Processing and Knowledge Engineering",
note = "7th International Conference on Natural Language Processing and Knowledge Engineering, NLP-KE 2011 ; Conference date: 27-11-2011 Through 29-11-2011",
}