Sentence extraction with topic modeling for question-answer pair generation
Gespeichert in:
Verfasser / Beitragende:
[Chung-Hsien Wu, Chao-Hong Liu, Po-Hsun Su]
Ort, Verlag, Jahr:
2015
Enthalten in:
Soft Computing, 19/1(2015-01-01), 39-46
Format:
Artikel (online)
Online Zugang:
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| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150101xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-014-1386-6 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1386-6 | ||
| 245 | 0 | 0 | |a Sentence extraction with topic modeling for question-answer pair generation |h [Elektronische Daten] |c [Chung-Hsien Wu, Chao-Hong Liu, Po-Hsun Su] |
| 520 | 3 | |a 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. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Sentence extraction |2 nationallicence | |
| 690 | 7 | |a Holism-based detection |2 nationallicence | |
| 690 | 7 | |a QA pair generation |2 nationallicence | |
| 690 | 7 | |a Topic modeling |2 nationallicence | |
| 700 | 1 | |a Wu |D Chung-Hsien |u Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan |4 aut | |
| 700 | 1 | |a Liu |D Chao-Hong |u ICL, Speech, Language and Audio Processing Department, Industrial Technology Research Institute, Hsinchu, Taiwan |4 aut | |
| 700 | 1 | |a Su |D Po-Hsun |u Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/1(2015-01-01), 39-46 |x 1432-7643 |q 19:1<39 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1386-6 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1386-6 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Wu |D Chung-Hsien |u Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Liu |D Chao-Hong |u ICL, Speech, Language and Audio Processing Department, Industrial Technology Research Institute, Hsinchu, Taiwan |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Su |D Po-Hsun |u Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/1(2015-01-01), 39-46 |x 1432-7643 |q 19:1<39 |1 2015 |2 19 |o 500 | ||