Extracting and Ranking Question-Focused Terms Using the Titles of Wikipedia Articles
Yi-Che Chan, Kuan-Hsi Chen, Wen‐Hsiang Lu · 2013
At the NTCIR-6 CLQA (Cross-Language Question Answering) task, we participated in the Chinese-Chinese (C-C) and English-Chinese (E-C) QA (Question Answering) subtasks. Without employing question type classification, we proposed a new resource, Wikipedia, to assist in extracting and ranking Question-Focused terms. We regarded the titles of Wikipedia articles as a multilingual noun-phrase corpus which is useful in QA systems. Experimental results showed that better performance was achieved for questions with type PERSON or LOCATION. Besides, we used an online MT (Machine Translation) system to deal with question translation in our CLQA task.