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A Bi-directional Evolution Algorithm for Financial Recommendation Model

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 768)

Abstract

By the challenge of rich data and poor information, recommender systems technology emerged as the time require and vigorous developed to more and more powerful vitality. However, in some real-world applications such as financial domain, the recommender systems of financial products usually require a long-term significant financial commitment as their utility, because it is not realized immediately depending on several external factors like market returns or governmental regularizations. In this paper, we propose a bi-direction evolution recommendation system (BDE_RS) to address this problem, which tries to balance the precision and the gains of the recommendation system. Portfolios are recommended based on the distance of investor and portfolio models which are composition of finite number financial assets with various weights. Based on investor transaction and investor profile, we design and construct recommendation using ARM technique for portfolio management. Extensive experiments conducted on benchmark and real-world data sets demonstrate that our proposed approach outperforms other state-of-the-art methods.

Keywords

Recommendation system BDE_RS Protfolio management 

Notes

Acknowledgments

This work was supported by the National Natural Science Foundation of China (Project no. 61303189, 61232016).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • Jingming Xue
    • 1
    • 2
  • Lu Huang
    • 3
  • Qiang Liu
    • 1
  • Jianping Yin
    • 1
  1. 1.College of ComputerNational University of Defense TechnologyChangshaChina
  2. 2.Bank of Changsha Co., Ltd.ChangshaChina
  3. 3.Department of ComputerChangSha Electric Power Technical CollegeChangshaChina

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