research-article

MultiGraph Attention Network for analyzing Company Relations

Authors:

Azadeh NematzadehAuthors Info & Claims

ICCPR '19: Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition

Pages 426 - 433

https://doi.org/10.1145/3373509.3373542

Published: 25 March 2020 Publication History

Abstract

When analyzing companies in financial markets, it is essential to identify those companies that share similar characteristics in order to assess their relative strengths and weaknesses. This challenging task requires representing the rich set of information associated with companies and the complex interrelations between them in a form that is amenable to pattern recognition. We present here a new deep representation learning method that encodes the network graph of companies in a low-dimensional embedding space, preserving its topological structure. Our solution employs a number of neural attention mechanisms that adaptively aggregate information over company node neighborhoods in a multi-dimensional edge setting. The learned company embeddings are transferable and can be fine-tuned for a wide range of analytical tasks. We demonstrate improvement over state-of-the-art solutions and illustrate the efficacy of our method for financial analysis tasks such as industry classification, peer group identification, credit rating anomaly detection and visualization of company relations.

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Cited By

Guo JJami AKröll MSchweizer LParamonov SAichinger ESferrazza SScaccia MReissfelder SCicek EGrasso GGottlob G(2023)When Automatic Filtering Comes to the Rescue: Pre-Computing Company Competitor Pairs in OwlerProceedings of the ACM on Management of Data10.1145/35897871:2(1-23)Online publication date: 20-Jun-2023
https://dl.acm.org/doi/10.1145/3589787
Noels SDe Ridder SViaene SDe Bie T(2023)An efficient graph‐based peer selection method for financial statementsIntelligent Systems in Accounting, Finance and Management10.1002/isaf.1539Online publication date: 5-Jul-2023
https://doi.org/10.1002/isaf.1539
Qin WLuo XWang H(2021)Implicit Business Competitor Inference Using Heterogeneous Knowledge Graph2021 IEEE International Conference on Big Knowledge (ICBK)10.1109/ICKG52313.2021.00035(198-205)Online publication date: Dec-2021
https://doi.org/10.1109/ICKG52313.2021.00035

Index Terms

MultiGraph Attention Network for analyzing Company Relations
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks
2. Information systems
  1. Information systems applications
    1. Decision support systems
      1. Data analytics

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ICCPR '19: Proceedings of the 2019 8th International Conference on Computing and Pattern Recognition

October 2019

522 pages

ISBN:9781450376570

DOI:10.1145/3373509

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Hebei University of Technology
Beijing University of Technology

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Association for Computing Machinery

New York, NY, United States

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Published: 25 March 2020

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ICCPR '19

ICCPR '19: 2019 8th International Conference on Computing and Pattern Recognition

October 23 - 25, 2019

Beijing, China

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Cited By

Guo JJami AKröll MSchweizer LParamonov SAichinger ESferrazza SScaccia MReissfelder SCicek EGrasso GGottlob G(2023)When Automatic Filtering Comes to the Rescue: Pre-Computing Company Competitor Pairs in OwlerProceedings of the ACM on Management of Data10.1145/35897871:2(1-23)Online publication date: 20-Jun-2023
https://dl.acm.org/doi/10.1145/3589787
Noels SDe Ridder SViaene SDe Bie T(2023)An efficient graph‐based peer selection method for financial statementsIntelligent Systems in Accounting, Finance and Management10.1002/isaf.1539Online publication date: 5-Jul-2023
https://doi.org/10.1002/isaf.1539
Qin WLuo XWang H(2021)Implicit Business Competitor Inference Using Heterogeneous Knowledge Graph2021 IEEE International Conference on Big Knowledge (ICBK)10.1109/ICKG52313.2021.00035(198-205)Online publication date: Dec-2021
https://doi.org/10.1109/ICKG52313.2021.00035

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