Cost-Effective Knowledge Graph Reasoning for Complex Factoid Questions

Xia Yang, Meng Fen Chiang, Wang Chien Lee, Yi Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The task of reasoning over knowledge graph for factoid questions has received significant interest from the research community of natural language processing. Performing this task inevitably faces the issues of question complexity and reasoning efficiency. In this paper, we investigate modern reasoning approaches over knowledge graph to tackle complex factoid questions of diverse reasoning schemas with attractive speedup in computational efficiency. To this end, we propose two evidence retrieval strategies to generate concise and informative evidence graph of high semantic-relevance and factual coverage to the question. Then, we adopt DELFT, a graph neural networks based framework that takes the linguistic structure representation of a question and the evidence graph as input, to predict the answer by reasoning over the evidence graph. We evaluate the performance across several baselines in terms of effectiveness and efficiency on two real-world datasets, MOOCQA and MetaQA. The results show the superiority of message passing paradigm in delivering a robust reasoner with better answer quality and significantly improved computational efficiency.

Original languageEnglish (US)
Title of host publicationIJCNN 2021 - International Joint Conference on Neural Networks, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9780738133669
StatePublished - Jul 18 2021
Event2021 International Joint Conference on Neural Networks, IJCNN 2021 - Virtual, Shenzhen, China
Duration: Jul 18 2021Jul 22 2021

Publication series

NameProceedings of the International Joint Conference on Neural Networks


Conference2021 International Joint Conference on Neural Networks, IJCNN 2021
CityVirtual, Shenzhen

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence


Dive into the research topics of 'Cost-Effective Knowledge Graph Reasoning for Complex Factoid Questions'. Together they form a unique fingerprint.

Cite this