TRANSLATION ASSISTANCE SYSTEM BASED ON SELECTIVE WEIGHTING AND CLUSTER-BASED SEARCHING METHODS

Abstract

Visiting a foreign country is now much easier than it was in the past. This has led to a consequent increase in the need for translation services during these visits. To satisfy this need, a reliable translation assistance system based on sentence retrieval techniques is proposed. When a user inputs a sentence in his/her native language, the proposed system retrieves sentences similar to the input sentence from a pre-constructed bilingual corpus and returns pairs of sentences in the native and foreign languages. To reduce the lexical disagreement problems that inevitably occur in this sentence retrieval application, the proposed system uses multi-level linguistic information (i.e., keywords, sentence types, and concepts) with different weights as indexing terms. In addition, the proposed system uses clustering information from sentences with similar meanings to smooth the retrieval target sentences. In an experiment, the proposed system outperformed traditional IR systems. Based on various experiments, it was found that multi-level information was effective at alleviating critical lexical disagreement problems in sentence retrieval. It was also found that the proposed system was suitable for sentence retrieval applications such as translation assistance systems.