TY - JOUR
T1 - Multiple Choice Question (MCQ) answering system for entrance examination
AU - Banerjee, Somnath
AU - Bhaskar, Pinaki
AU - Pakray, Partha
AU - Bandyopadhyay, Sivaji
AU - Gelbukh, Alexander
PY - 2013
Y1 - 2013
N2 - The article presents the experiments carried out as part of the participation in the pilot task of QA4MRE@CLEF 2013. In the developed system, we have first generated answer pattern by combining the question and each answer option to form the Hypothesis (H). Stop words and interrogative word are removed from each H and query words are identified to retrieve the most relevant sentences from the associated document using Lucene. Relevant sentences are retrieved from the associated document based on the TF-IDF of the matching query words along with n-gram overlap of the sentence with the H. Each retrieved sentence defines the Text T. Each T-H pair is assigned a ranking score that works on textual entailment principle. A matching score is automatically assigned to each answer options based on the matching. A parallel procedure also generates the possible answer patterns from given questions and answer options. Each sentence in the associated document is assigned an inference score with respect to each answer pattern. Evaluated inference score for each answer option is added with the matching score. The answer option that receives the highest selection score is identified as the most relevant option and selected as the answer to the given question.
AB - The article presents the experiments carried out as part of the participation in the pilot task of QA4MRE@CLEF 2013. In the developed system, we have first generated answer pattern by combining the question and each answer option to form the Hypothesis (H). Stop words and interrogative word are removed from each H and query words are identified to retrieve the most relevant sentences from the associated document using Lucene. Relevant sentences are retrieved from the associated document based on the TF-IDF of the matching query words along with n-gram overlap of the sentence with the H. Each retrieved sentence defines the Text T. Each T-H pair is assigned a ranking score that works on textual entailment principle. A matching score is automatically assigned to each answer options based on the matching. A parallel procedure also generates the possible answer patterns from given questions and answer options. Each sentence in the associated document is assigned an inference score with respect to each answer pattern. Evaluated inference score for each answer option is added with the matching score. The answer option that receives the highest selection score is identified as the most relevant option and selected as the answer to the given question.
KW - Named entity
KW - QA4MRE data sets
KW - Question answering technique
KW - Textual entailment
UR - http://www.scopus.com/inward/record.url?scp=84922032568&partnerID=8YFLogxK
M3 - Artículo de la conferencia
AN - SCOPUS:84922032568
SN - 1613-0073
VL - 1179
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 2013 Cross Language Evaluation Forum Conference, CLEF 2013
Y2 - 23 September 2013 through 26 September 2013
ER -