Difference between revisions of "Extracting and Ranking Question-Focused Terms Using the Titles of Wikipedia Articles"
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+ | | title = Extracting and Ranking Question-Focused Terms Using the Titles of Wikipedia Articles | ||
+ | | date = 2007 | ||
+ | | authors = [[Yi-Che Chan]]<br />[[Kuan-Hsi Chen]]<br />[[Wen Hsiang Lu]] | ||
+ | | link = http://research.nii.ac.jp/ntcir/ntcir-ws6/OnlineProceedings/NTCIR/58.pdf | ||
+ | }} | ||
'''Extracting and Ranking Question-Focused Terms Using the Titles of Wikipedia Articles''' - scientific work related to [[Wikipedia quality]] published in 2007, written by [[Yi-Che Chan]], [[Kuan-Hsi Chen]] and [[Wen Hsiang Lu]]. | '''Extracting and Ranking Question-Focused Terms Using the Titles of Wikipedia Articles''' - scientific work related to [[Wikipedia quality]] published in 2007, written by [[Yi-Che Chan]], [[Kuan-Hsi Chen]] and [[Wen Hsiang Lu]]. | ||
== Overview == | == Overview == | ||
At the NTCIR-6 CLQA (Cross-Language Question Answering) task, authors participated in the Chinese-Chinese (C-C) and English-Chinese (E-C) QA (Question Answering) subtasks. Without employing question type classification, authors proposed a new resource, [[Wikipedia]], to assist in extracting and ranking Question-Focused terms. Authors 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, authors used an online MT (Machine Translation) system to deal with question translation in CLQA task. | At the NTCIR-6 CLQA (Cross-Language Question Answering) task, authors participated in the Chinese-Chinese (C-C) and English-Chinese (E-C) QA (Question Answering) subtasks. Without employing question type classification, authors proposed a new resource, [[Wikipedia]], to assist in extracting and ranking Question-Focused terms. Authors 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, authors used an online MT (Machine Translation) system to deal with question translation in CLQA task. |
Revision as of 11:34, 20 June 2019
Authors | Yi-Che Chan Kuan-Hsi Chen Wen Hsiang Lu |
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Publication date | 2007 |
Links | Original |
Extracting and Ranking Question-Focused Terms Using the Titles of Wikipedia Articles - scientific work related to Wikipedia quality published in 2007, written by Yi-Che Chan, Kuan-Hsi Chen and Wen Hsiang Lu.
Overview
At the NTCIR-6 CLQA (Cross-Language Question Answering) task, authors participated in the Chinese-Chinese (C-C) and English-Chinese (E-C) QA (Question Answering) subtasks. Without employing question type classification, authors proposed a new resource, Wikipedia, to assist in extracting and ranking Question-Focused terms. Authors 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, authors used an online MT (Machine Translation) system to deal with question translation in CLQA task.