QRpotato: a system that exhaustively collects bilingual technical term pairs from the web

Abstract

This paper reports the system QRpotato, which exhaustively collects bilingual technical term pairs from the Web. The system uses bilingual (Japanese-English) term pairs taken from existing terminological dictionary as seed pairs, search Web pages using the seed pairs, and extract bilingual term pair candidates from the retrieved Web pages, using relational patterns identified between seed term pairs. We have successfully collected about 2.2 million different term pair candidates by using about 210,000 seed term pairs. The manual evaluation of the parts of the candidates shows the effectiveness of the method.