P2P Lending Analysis Using the Most Relevant Graph-Based Features

Lixin Cui; Lu Bai; Yue Wang; Xiao Bai; Zhihong Zhang; Edwin R. Hancock

doi:10.1007/978-3-319-49055-7_1

P2P Lending Analysis Using the Most Relevant Graph-Based Features

Lixin Cui, Lu Bai, Yue Wang, Xiao Bai, Zhihong Zhang, Edwin R. Hancock

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings
Publisher	Springer
Pages	3-14
Number of pages	12
ISBN (Print)	97833194905571
DOIs	https://doi.org/10.1007/978-3-319-49055-7_1
Publication status	Published - 8 Nov 2016

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	10029
ISSN (Print)	0302-9743

Bibliographical note

© 2016 Springer International Publishing AG, 2016. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

Access to Document

10.1007/978-3-319-49055-7_1

paper_30 (1)
© 2016 Springer International Publishing AG, 2016. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details (no embargo)
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Cite this

Cui, L., Bai, L., Wang, Y., Bai, X., Zhang, Z., & Hancock, E. R. (2016). P2P Lending Analysis Using the Most Relevant Graph-Based Features. In Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings (pp. 3-14). (Lecture Notes in Computer Science; Vol. 10029). Springer. https://doi.org/10.1007/978-3-319-49055-7_1

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Cui, L, Bai, L, Wang, Y, Bai, X, Zhang, Z & Hancock, ER 2016, P2P Lending Analysis Using the Most Relevant Graph-Based Features. in Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings. Lecture Notes in Computer Science, vol. 10029, Springer, pp. 3-14. https://doi.org/10.1007/978-3-319-49055-7_1

P2P Lending Analysis Using the Most Relevant Graph-Based Features. / Cui, Lixin; Bai, Lu; Wang, Yue et al.
Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings. Springer, 2016. p. 3-14 (Lecture Notes in Computer Science; Vol. 10029).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - P2P Lending Analysis Using the Most Relevant Graph-Based Features

AU - Cui, Lixin

AU - Bai, Lu

AU - Wang, Yue

AU - Bai, Xiao

AU - Zhang, Zhihong

AU - Hancock, Edwin R.

N1 - © 2016 Springer International Publishing AG, 2016. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

PY - 2016/11/8

Y1 - 2016/11/8

U2 - 10.1007/978-3-319-49055-7_1

DO - 10.1007/978-3-319-49055-7_1

M3 - Conference contribution

SN - 97833194905571

T3 - Lecture Notes in Computer Science

SP - 3

EP - 14

BT - Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings

PB - Springer

ER -

Cui L, Bai L, Wang Y, Bai X, Zhang Z, Hancock ER. P2P Lending Analysis Using the Most Relevant Graph-Based Features. In Structural, Syntactic, and Statistical Pattern Recognition - Joint IAPR International Workshop, S+SSPR 2016, Mérida, Mexico, November 29 - December 2, 2016, Proceedings. Springer. 2016. p. 3-14. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-49055-7_1