DocumentCode :
1780542
Title :
Automatic Question Generation system
Author :
Pabitha, P. ; Mohana, M. ; Suganthi, S. ; Sivanandhini, B.
Author_Institution :
Dept. of Comput. Technol., Anna Univ., Chennai, India
fYear :
2014
fDate :
10-12 April 2014
Firstpage :
1
Lastpage :
5
Abstract :
The process of automating the question generation consists of many tasks. Selecting the target content (what to ask), question type (who, why, how) and actual question generation are the major issue of Automatic Question Generation. Certain definitions retrieved is available in Wikipedia either directly or is the outcome of executing set of sub queries for each key phrase categories The problem in the existing system is that some of the definition sentences which are taken out from Wikipedia were implicit. The proposed system overcomes the problems by using Supervised Learning Approach, Naïve Bayes method. It also extends its work to use Summarization, Noun Filtering and Question Generation in the aim of generating semantically correct questions.
Keywords :
Bayes methods; Web sites; information filtering; learning (artificial intelligence); query processing; question answering (information retrieval); text analysis; Wikipedia; automatic question generation system; definition sentences; key phrase categories; naïve Bayes method; noun filtering; question type; subqueries; summarization; supervised learning approach; Data mining; Information filters; Information services; Information technology; Market research; Automatic Question Generation; Key phrases; Naïve Bayes; Noun Filtering; Stemming; Summarization; Supervised Machine Learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Recent Trends in Information Technology (ICRTIT), 2014 International Conference on
Conference_Location :
Chennai
Type :
conf
DOI :
10.1109/ICRTIT.2014.6996216
Filename :
6996216
Link To Document :
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