TY - GEN
T1 - Identifying informational vs. conversational qestions on community qestion answering archives
AU - Guy, Ido
AU - Makarenkov, Victor
AU - Hazon, Niva
AU - Rokach, Lior
AU - Shapira, Bracha
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/2/2
Y1 - 2018/2/2
N2 - Questions on community question answering websites usually reflect one of two intents: learning information or starting a conversation. In this paper, we revisit this fundamental classification task of informational versus conversational questions, which was originally introduced and studied in 2009. We use a substantially larger dataset of archived questions from Yahoo Answers, which includes the question's title, description, answers, and votes. We replicate the original experiments over this dataset, point out the common and different from the original results, and present a broad set of characteristics that distinguish the two question types. We also develop new classifiers that make use of additional data types, advanced machine learning, and a large dataset of unlabeled data, which achieve enhanced performance.
AB - Questions on community question answering websites usually reflect one of two intents: learning information or starting a conversation. In this paper, we revisit this fundamental classification task of informational versus conversational questions, which was originally introduced and studied in 2009. We use a substantially larger dataset of archived questions from Yahoo Answers, which includes the question's title, description, answers, and votes. We replicate the original experiments over this dataset, point out the common and different from the original results, and present a broad set of characteristics that distinguish the two question types. We also develop new classifiers that make use of additional data types, advanced machine learning, and a large dataset of unlabeled data, which achieve enhanced performance.
UR - http://www.scopus.com/inward/record.url?scp=85046907676&partnerID=8YFLogxK
U2 - 10.1145/3159652.3159733
DO - 10.1145/3159652.3159733
M3 - Conference contribution
AN - SCOPUS:85046907676
T3 - WSDM 2018 - Proceedings of the 11th ACM International Conference on Web Search and Data Mining
SP - 216
EP - 224
BT - WSDM 2018 - Proceedings of the 11th ACM International Conference on Web Search and Data Mining
PB - Association for Computing Machinery, Inc
T2 - 11th ACM International Conference on Web Search and Data Mining, WSDM 2018
Y2 - 5 February 2018 through 9 February 2018
ER -