TY - GEN
T1 - Word/phrase based answer type classification for Bengali question answering system
AU - Islam, Md Aminul
AU - Kabir, Md Fasihul
AU - Abdullah-Al-Mamun, Khandaker
AU - Huda, Mohammad Nurul
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/28
Y1 - 2016/11/28
N2 - This paper work demonstrated an analytical ability of question answer type classification steps towards building a question answering system in Bengali language. In order to respond correctly to a free form factoid question or complex questions given a large collection of corpus, one needs to understand the question category that allows determining some of the constraints the question imposes on a possible answer. Question classification (QC) Systems allows the user to ask questions in a natural language and acquire a correct answer category (AC). This work presents the first work on a machine learning approach to Bengali question classification using stochastic gradient descent (SGD) classifier method. Stochastic gradient descent is a gradient descent optimization method for minimizing an objective function that is written as a sum of differentiable functions. Our system based on stochastic gradient descent (SGD) classifier achieved average precision 0.95562 for coarse and 0.87646 for finer.
AB - This paper work demonstrated an analytical ability of question answer type classification steps towards building a question answering system in Bengali language. In order to respond correctly to a free form factoid question or complex questions given a large collection of corpus, one needs to understand the question category that allows determining some of the constraints the question imposes on a possible answer. Question classification (QC) Systems allows the user to ask questions in a natural language and acquire a correct answer category (AC). This work presents the first work on a machine learning approach to Bengali question classification using stochastic gradient descent (SGD) classifier method. Stochastic gradient descent is a gradient descent optimization method for minimizing an objective function that is written as a sum of differentiable functions. Our system based on stochastic gradient descent (SGD) classifier achieved average precision 0.95562 for coarse and 0.87646 for finer.
UR - http://www.scopus.com/inward/record.url?scp=85007240874&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85007240874&partnerID=8YFLogxK
U2 - 10.1109/ICIEV.2016.7760043
DO - 10.1109/ICIEV.2016.7760043
M3 - Conference contribution
AN - SCOPUS:85007240874
T3 - 2016 5th International Conference on Informatics, Electronics and Vision, ICIEV 2016
SP - 445
EP - 448
BT - 2016 5th International Conference on Informatics, Electronics and Vision, ICIEV 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th International Conference on Informatics, Electronics and Vision, ICIEV 2016
Y2 - 13 May 2016 through 14 May 2016
ER -