Efficient SPARQL Queries Generator for Question Answering Systems
Much like traditional database querying, the question answering process in a Question Answering (QA) system involves converting a user’s question input into query grammar, querying the knowledge base through the query grammar, and finally returning the query result (i.e., the answer) to t...
Main Authors: | Yi-Hui Chen, Eric Jui-Lin Lu, Ying-Yen Lin |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9893129/ |
Similar Items
-
Intelligent SPARQL Query Generation for Natural Language Processing Systems
by: Yi-Hui Chen, et al.
Published: (2021-01-01) -
Finding and sharing GIS methods based on the questions they answer
by: S. Scheider, et al.
Published: (2019-05-01) -
Enhancing SPARQL Query Performance With Recurrent Neural Networks
by: Yi-Hui Chen, et al.
Published: (2023-01-01) -
Enhancing SPARQL Query Generation for Knowledge Base Question Answering Systems by Learning to Correct Triplets
by: Jiexing Qi, et al.
Published: (2024-02-01) -
QA4PRF: A Question Answering Based Framework for Pseudo Relevance Feedback
by: Handong Ma, et al.
Published: (2021-01-01)