The Joint Method of Triple Attention and Novel Loss Function for Entity Relation Extraction in Small Data-Driven Computational Social Systems-Reference-Cited by-同舟云学术

The Joint Method of Triple Attention and Novel Loss Function for Entity Relation Extraction in Small Data-Driven Computational Social Systems

Published:2022-12 Issue:6 Volume:9 Page:1725-1735
ISSN:2329-924X
Container-title:IEEE Transactions on Computational Social Systems
language:
Short-container-title:IEEE Trans. Comput. Soc. Syst.

Author:

Gao Honghao¹^ORCID,Huang Jiadong¹,Tao Yuan¹,Hussain Walayat²^ORCID,Huang Yuzhe¹^ORCID

Affiliation:

1. School of Computer Engineering and Science, Shanghai University, Shanghai, China

2. Victoria University Business School, Victoria University, Melbourne, VIC, Australia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation

Link

http://xplorestaging.ieee.org/ielx7/6570650/9966856/09791432.pdf?arnumber=9791432

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4. Learning to Compare: Relation Network for Few-Shot Learning

5. Matching networks for one shot learning;vinyals;Proc Adv Neural Inf Process Syst,2016

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