Learning weights for translation candidates in Japanese–Chinese information retrieval

Abstract

This paper describes our Japanese–Chinese information retrieval system. Our system takes the “query-translation” approach. Our system employs both a more conventional bilingual Japanese–Chinese dictionary and Wikipedia for translating query terms. We propose that Wikipedia can be used as a good NE bilingual dictionary. By exploiting the nature of Japanese writing system, we propose that query terms be processed differently based on the forms they are written in. We use an iterative method for weight-tuning and term disambiguation, which is based on the PageRank algorithm. When evaluating on the NTCIR-5 test set, our system achieves as high as 0.2217 and 0.2276 in relax MAP (mean average precision) measurement of T-runs and D-runs.