TY - JOUR
T1 - Automatic question generation
AU - Last, Mark
AU - Danon, Guy
N1 - Funding Information:
This research was partially supported by IBM Cyber Security Center of Excellence (CCoE), Beer Sheva, Israel under grant no. 15/12/144.
Publisher Copyright:
© 2020 Wiley Periodicals LLC.
PY - 2020/11/1
Y1 - 2020/11/1
N2 - Automatic generation of semantically well-formed questions from a given text can contribute to various domains, including education, dialogues/interactive question answering systems, search engines, and more. It is well-known as a challenging task, which involves the common obstacles of other natural language processing (NLP) activities. We start this advanced review with a brief overview of the most common automatic question generation (AQG) applications. Then we describe the main steps of a typical AQG pipeline, namely question construction, ranking, and evaluation. Finally, we discuss the open challenges of the AQG field that still need to be addressed by NLP researchers. This article is categorized under: Algorithmic Development > Text Mining.
AB - Automatic generation of semantically well-formed questions from a given text can contribute to various domains, including education, dialogues/interactive question answering systems, search engines, and more. It is well-known as a challenging task, which involves the common obstacles of other natural language processing (NLP) activities. We start this advanced review with a brief overview of the most common automatic question generation (AQG) applications. Then we describe the main steps of a typical AQG pipeline, namely question construction, ranking, and evaluation. Finally, we discuss the open challenges of the AQG field that still need to be addressed by NLP researchers. This article is categorized under: Algorithmic Development > Text Mining.
KW - automated question generation
KW - natural language generation
UR - http://www.scopus.com/inward/record.url?scp=85088593909&partnerID=8YFLogxK
U2 - 10.1002/widm.1382
DO - 10.1002/widm.1382
M3 - Review article
AN - SCOPUS:85088593909
SN - 1942-4787
VL - 10
JO - Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
JF - Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
IS - 6
M1 - e1382
ER -