Automatic Training Corpora Acquisition through Web Mining
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Text classification by labeling words
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
QRpotato: a system that exhaustively collects bilingual technical term pairs from the web
Proceedings of the 3rd International Universal Communication Symposium
QRselect: a user-driven system for collecting translation document pairs from the web
ICADL'07 Proceedings of the 10th international conference on Asian digital libraries: looking back 10 years and forging new frontiers
Hi-index | 0.00 |
This paper proposes a method of domain specificity estimation of technical terms using the Web. In the proposed method, it is assumed that, for a certain technical domain, a list of known technical terms of the domain is given. Technical documents of the domain are collected through the Web search engine, which are then used for generating a vector space model for the domain. The domain specificity of a target term is estimated according to the distribution of the domain of the sample pages of the target term. We apply this technique of estimating domain specificity of a term to the task of discovering novel technical terms that are not included in any of existing lexicons of technical terms of the domain. Out of randomly selected 1,000 candidates of technical terms per a domain, we discovered about 100 ~ 200 novel technical terms.