Special section: Information Retrieval and Natural Language Processing

 

English–to–Japanese Cross–Language Question–Answering System using Weighted Adding with Multiple Answers

 

Masaki Murata, Masao Utiyama, Toshiyuki Kanamaru, and Hitoshi Isahara

 

National Institute of Information and Communications Technology 3–5 Hikaridai, Seika–cho, Soraku–gun, Kyoto, 619–0289, Japan (e–mail: murata@nict.go.jp).

 

Manuscript received October 19, 2008.
Manuscript accepted for publication August 3, 2009.

 

Abstract

We describe a method of using multiple documents with decreasing weights as evidence to improve the performance of a question–answering system. We also describe how it was used in cross–language question answering (CLQA) tasks. Sometimes, the answer to a question may be found in multiple documents. In such cases, using multiple documents for prediction generates better answers than using a single document. Therefore, our method uses information from multiple documents by adding the scores of candidate answers extracted from the various documents. Because simply adding scores degrades the performance of question–answering systems, we add scores with decreasing weights to reduce the negative effect of simply adding. We used this method in the CLQA part of NTCIR–5. It was incorporated into a commercially available translation system that carries out cross–language question–answering tasks. Our method obtained relatively good CLQA results.

Key words: Machine translation, cross–language question–answering, decreased adding, multiple documents, NTCIR.

 

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