Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
11-2019
Abstract
Knowledge Base Question Answering (KBQA) has attracted much attention and recently there has been more interest in multi-hop KBQA. In this paper, we propose a novel iterative sequence matching model to address several limitations of previous methods for multi-hop KBQA. Our method iteratively grows the candidate relation paths that may lead to answer entities. The method prunes away less relevant branches and incrementally assigns matching scores to the paths. Empirical results demonstrate that our method can significantly outperform existing methods on three different benchmark datasets.
Keywords
knowledge base question answering, sequence matching model, multi-hop question answering
Discipline
Computer Sciences
Research Areas
Data Science and Engineering
Publication
Proceedings of the IEEE International Conference on Data Mining
Identifier
10.1109/ICDM.2019.00046
Publisher
IEEE
City or Country
Beijing, China
Citation
LAN, Yunshi; WANG, Shuohang; and JIANG, Jing.
Multi-hop knowledge base question answering with an iterative sequence matching model. (2019). Proceedings of the IEEE International Conference on Data Mining.
Available at: https://ink.library.smu.edu.sg/sis_research/4936
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/ICDM.2019.00046