This paper presents additional linguistic factors that should be considered to more effectively extract terms from the machinery industry documents by augmenting the general extraction patterns. We expand on the general term extraction patterns with patterns that are tailored for machinery industry documents to improve precision and recall. We establish a theoretical basis for developing a system to support information research in the machinery industry. Using this system, we expect to increase the efficiency of new business planning process in the machine industry.
Improved named entity translation and bilingual named entity extraction
