What is it about?
We proposed a knowledge reasoning model based on non-factoid information enhancement (NFE-KRM) in scenic Q&A. It realizes the KGE integrates semantic information (SIKGE) and the unified semantic embedding space (USES), so that NFE-KRM has the ability to answer both factoid and non-factoid questions.
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Why is it important?
We have used a large number of experiments to prove that SIKGE gets a better performance on Mean Rank and Hits@10. NFE-KRM's F1 score and accuracy on the mixed dataset are both competitive. What’s more, in the light of our robot had generated certain economic and social benefits, 2022 China International Fair for Trade in Services (2022CIFTIS) invited it to participate in the exhibition.
Perspectives
I hope this article can provide new ideas for researchers exploring human-machine dialogue, making the communication between robots and humans smoother, humanoid, more knowledgeable, and more emotionally identified.
Sa Xu
Beijing University of Posts and Telecommunications
Read the Original
This page is a summary of: A Knowledge Reasoning Model Based on Non-Factoid Information Enhancement, December 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3582197.3582250.
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