Group Recommendation Based on Financial Social Network for Robo-Advisor
Robo-advisor is a financial advisor that can get help from machine-learning algorithms to automatically analyze financial product risk levels and provide portfolio recommendations. In the previous work, robo-advisor mainly focused on the basic information and investment preferences of individual use...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8470063/ |
| _version_ | 1818914532376969216 |
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| author | Jingming Xue En Zhu Qiang Liu Jianping Yin |
| author_facet | Jingming Xue En Zhu Qiang Liu Jianping Yin |
| author_sort | Jingming Xue |
| collection | DOAJ |
| description | Robo-advisor is a financial advisor that can get help from machine-learning algorithms to automatically analyze financial product risk levels and provide portfolio recommendations. In the previous work, robo-advisor mainly focused on the basic information and investment preferences of individual users and often ignored the relationship between groups and the individual's risk preference. In the actual environment, the individual investment behavior and the group's social relations are inseparable. In order to solve this challenge, this paper proposes a group recommendation model based on financial social networks and collaborative filtering algorithms. Compared with the latest personalized recommendation system, it not only considers the asset status and risk level of individual investors but also considers social relationships and risk levels among groups. With experiments on benchmark and real-world datasets, we demonstrate that the proposed algorithm achieves the superior performance on both the tasks compared to the state-of-the-art methods. |
| first_indexed | 2024-12-19T23:47:53Z |
| format | Article |
| id | doaj.art-b7070f49fcdc4f9ca0c99b05f0468ffb |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T23:47:53Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-b7070f49fcdc4f9ca0c99b05f0468ffb2022-12-21T20:01:15ZengIEEEIEEE Access2169-35362018-01-016545275453510.1109/ACCESS.2018.28711318470063Group Recommendation Based on Financial Social Network for Robo-AdvisorJingming Xue0https://orcid.org/0000-0002-8716-5523En Zhu1Qiang Liu2https://orcid.org/0000-0003-2922-3518Jianping Yin3College of Computer, National University of Defense Technology, Changsha, ChinaCollege of Computer, National University of Defense Technology, Changsha, ChinaCollege of Computer, National University of Defense Technology, Changsha, ChinaCollege of Computer, Dongguan University of Technology, Dongguan, ChinaRobo-advisor is a financial advisor that can get help from machine-learning algorithms to automatically analyze financial product risk levels and provide portfolio recommendations. In the previous work, robo-advisor mainly focused on the basic information and investment preferences of individual users and often ignored the relationship between groups and the individual's risk preference. In the actual environment, the individual investment behavior and the group's social relations are inseparable. In order to solve this challenge, this paper proposes a group recommendation model based on financial social networks and collaborative filtering algorithms. Compared with the latest personalized recommendation system, it not only considers the asset status and risk level of individual investors but also considers social relationships and risk levels among groups. With experiments on benchmark and real-world datasets, we demonstrate that the proposed algorithm achieves the superior performance on both the tasks compared to the state-of-the-art methods.https://ieeexplore.ieee.org/document/8470063/Asset allocationsocial networkcollaborative filteringgroup recommender systems |
| spellingShingle | Jingming Xue En Zhu Qiang Liu Jianping Yin Group Recommendation Based on Financial Social Network for Robo-Advisor IEEE Access Asset allocation social network collaborative filtering group recommender systems |
| title | Group Recommendation Based on Financial Social Network for Robo-Advisor |
| title_full | Group Recommendation Based on Financial Social Network for Robo-Advisor |
| title_fullStr | Group Recommendation Based on Financial Social Network for Robo-Advisor |
| title_full_unstemmed | Group Recommendation Based on Financial Social Network for Robo-Advisor |
| title_short | Group Recommendation Based on Financial Social Network for Robo-Advisor |
| title_sort | group recommendation based on financial social network for robo advisor |
| topic | Asset allocation social network collaborative filtering group recommender systems |
| url | https://ieeexplore.ieee.org/document/8470063/ |
| work_keys_str_mv | AT jingmingxue grouprecommendationbasedonfinancialsocialnetworkforroboadvisor AT enzhu grouprecommendationbasedonfinancialsocialnetworkforroboadvisor AT qiangliu grouprecommendationbasedonfinancialsocialnetworkforroboadvisor AT jianpingyin grouprecommendationbasedonfinancialsocialnetworkforroboadvisor |