TY  - JOUR
T1  - Key Phrase Extraction Using Naive Bayes’ in Question Generation System
AU - Pabitha, P. AU - Suganthi, S. AU - Ram, Raja 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 3
SP  - 372
EP  - 375
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.372.375
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.372.375
KW  - Key phrases
KW  -supervised machine learning
KW  -naive bayes
KW  -stemming
KW  -automatic question generation
AB  - Automatic Question Generation (AQG) is a challenging task which involves many difficulties. The major aspects of automatic question generation are selecting the target content (what to ask), question type (who, why, how) and actual question generation. The problem encountered in the existing system was that some of the definition sentences are extracted from Wikipedia which were implicit or matched with multiple rules from different key phrase categories. Another limitation is that it is domain dependent and may not apply this approach to other applications such as reading comprehension. The proposed system overcomes the problems by using supervised learning approach. It also extends its work to applications like reading comprehension. The computers can read the submitted documents. The proposed system initially stems the document. The system extracts the key phrases from the documents through its knowledge. Each key phrase is matched with the database.
ER  -