Collecting Novel Technical Terms from the Web by Estimating Domain Specificity of a Term

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.