Sentence extraction with topic modeling for question–answer pair generation

Chung Hsien Wu, Chao Hong Liu, Po Hsun Su

研究成果: Article同行評審

7 引文 斯高帕斯(Scopus)

摘要

Recently, automatic QA pair generation has been an essential technique to reduce human involvement in the construction of QA systems. In a big data era, huge information is produced every day. Therefore, it is an important issue for QA systems to be able to respond to users with up-to-date information, e.g., to answer questions regarding recent posts on blogs. The major problem in building such systems is the efficiency to capture relevant text sources for specific QA domains. In this study, topic modeling is used as a means to help determine efficiently if an article is of the same topic as a specific domain of interest, e.g., health domain as exemplified in this paper. QA pairs are then generated from these selected articles using the proposed sentence extraction method. Experimental results show that, using the proposed method with topic modeling, a 7.3 % acceptance rate improvement on the generated questions was achieved.

原文English
頁(從 - 到)39-46
頁數8
期刊Soft Computing
19
發行號1
DOIs
出版狀態Published - 2014 1月

All Science Journal Classification (ASJC) codes

  • 理論電腦科學
  • 軟體
  • 幾何和拓撲

指紋

深入研究「Sentence extraction with topic modeling for question–answer pair generation」主題。共同形成了獨特的指紋。

引用此