CLC number: TP391
On-line Access: 2023-03-25
Received: 2022-04-14
Revision Accepted: 2023-03-25
Crosschecked: 2022-12-01
Cited: 0
Clicked: 1738
Citations: Bibtex RefMan EndNote GB/T7714
Qianqiao LIANG, Hua WEI, Yaxi WU, Feng WEI, Deng ZHAO, Jianshan HE, Xiaolin ZHENG, Guofang MA, Bing HAN. Exploring financially constrained small- and medium-sized enterprises based on a multi-relation translational graph attention network[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(3): 388-402.
@article{title="Exploring financially constrained small- and medium-sized enterprises based on a multi-relation translational graph attention network",
author="Qianqiao LIANG, Hua WEI, Yaxi WU, Feng WEI, Deng ZHAO, Jianshan HE, Xiaolin ZHENG, Guofang MA, Bing HAN",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="24",
number="3",
pages="388-402",
year="2023",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2200151"
}
%0 Journal Article
%T Exploring financially constrained small- and medium-sized enterprises based on a multi-relation translational graph attention network
%A Qianqiao LIANG
%A Hua WEI
%A Yaxi WU
%A Feng WEI
%A Deng ZHAO
%A Jianshan HE
%A Xiaolin ZHENG
%A Guofang MA
%A Bing HAN
%J Frontiers of Information Technology & Electronic Engineering
%V 24
%N 3
%P 388-402
%@ 2095-9184
%D 2023
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2200151
TY - JOUR
T1 - Exploring financially constrained small- and medium-sized enterprises based on a multi-relation translational graph attention network
A1 - Qianqiao LIANG
A1 - Hua WEI
A1 - Yaxi WU
A1 - Feng WEI
A1 - Deng ZHAO
A1 - Jianshan HE
A1 - Xiaolin ZHENG
A1 - Guofang MA
A1 - Bing HAN
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 24
IS - 3
SP - 388
EP - 402
%@ 2095-9184
Y1 - 2023
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2200151
Abstract: financing needs exploration (FNE), which explores financially constrained small- and medium-sized enterprises (SMEs), has become increasingly important in industry for financial institutions to facilitate SMEs' development. In this paper, we first perform an insightful exploratory analysis to exploit the transfer phenomenon of financing needs among SMEs, which motivates us to fully exploit the multi-relation enterprise social network for boosting the effectiveness of FNE. The main challenge lies in modeling two kinds of heterogeneity, i.e., transfer heterogeneity and SMEs' behavior heterogeneity, under different relation types simultaneously. To address these challenges, we propose a graph neural network named Multi-relation tRanslatIonal GrapH aTtention network (M-RIGHT), which not only models the transfer heterogeneity of financing needs along different relation types based on a novel entity–relation composition operator but also enables heterogeneous SMEs' representations based on a translation mechanism on relational hyperplanes to distinguish SMEs' heterogeneous behaviors under different relation types. Extensive experiments on two large-scale real-world datasets demonstrate M-RIGHT's superiority over the state-of-the-art methods in the FNE task.
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