TY - GEN
T1 - Mutual relation detection for complex question answering over knowledge graph
AU - Zhang, Qifan
AU - Tong, Peihao
AU - Yao, Junjie
AU - Wang, Xiaoling
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2020.
PY - 2020
Y1 - 2020
N2 - Question Answering over Knowledge Graph (KG-QA) becomes a convenient way to interact with the prevailing information. The user’s information needs, i.e., input questions become more complex. We find that the comparison, relation, and opinion questions are witnessed a significant growth, especially in some domains. However, most of the current KG-QA methods cannot appropriately handle the inherent complex relation and coverage characteristics within the questions. In this work, we propose to utilize the relation information with the questions and knowledge graph in a mutual way, improving the final question answering performance. Wse design local and global attention models for relation detection. We combine the features for relation detection in an attention matching model. Experiments on our new dataset and common dataset reveal its advantages both in accuracy and efficiency.
AB - Question Answering over Knowledge Graph (KG-QA) becomes a convenient way to interact with the prevailing information. The user’s information needs, i.e., input questions become more complex. We find that the comparison, relation, and opinion questions are witnessed a significant growth, especially in some domains. However, most of the current KG-QA methods cannot appropriately handle the inherent complex relation and coverage characteristics within the questions. In this work, we propose to utilize the relation information with the questions and knowledge graph in a mutual way, improving the final question answering performance. Wse design local and global attention models for relation detection. We combine the features for relation detection in an attention matching model. Experiments on our new dataset and common dataset reveal its advantages both in accuracy and efficiency.
UR - https://www.scopus.com/pages/publications/85092076378
U2 - 10.1007/978-3-030-59416-9_38
DO - 10.1007/978-3-030-59416-9_38
M3 - 会议稿件
AN - SCOPUS:85092076378
SN - 9783030594152
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 623
EP - 631
BT - Database Systems for Advanced Applications - 25th International Conference, DASFAA 2020, Proceedings
A2 - Nah, Yunmook
A2 - Cui, Bin
A2 - Lee, Sang-Won
A2 - Yu, Jeffrey Xu
A2 - Moon, Yang-Sae
A2 - Whang, Steven Euijong
PB - Springer Science and Business Media Deutschland GmbH
T2 - 25th International Conference on Database Systems for Advanced Applications, DASFAA 2020
Y2 - 24 September 2020 through 27 September 2020
ER -