Question Classification with Deep Contextualized Transformer
October 17, 2019 ยท Declared Dead ยท ๐ Advances in Intelligent Systems and Computing
"No code URL or promise found in abstract"
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Authors
Haozheng Luo, Ningwei Liu, Charles Feng
arXiv ID
1910.10492
Category
cs.CL: Computation & Language
Cross-listed
cs.AI
Citations
2
Venue
Advances in Intelligent Systems and Computing
Last Checked
5 months ago
Abstract
The latest work for Question and Answer problems is to use the Stanford Parse Tree. We build on prior work and develop a new method to handle the Question and Answer problem with the Deep Contextualized Transformer to manage some aberrant expressions. We also conduct extensive evaluations of the SQuAD and SwDA dataset and show significant improvement over QA problem classification of industry needs. We also investigate the impact of different models for the accuracy and efficiency of the problem answers. It shows that our new method is more effective for solving QA problems with higher accuracy
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