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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (8): 39-47    DOI: 10.11925/infotech.2096-3467.2017.08.05
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Collaboration Recommendation of Finance Research Based on Multi-feature Fusion
Yu Chuanming1, Gong Yutian1, Zhao Xiaoli1, An Lu2()
1School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China
2School of Information Management, Wuhan University, Wuhan 430072, China
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Abstract  

[Objective] Research collaboration builds an important social network system. This paper proposes a new recommendation model for research collaboration in finance, aiming to promote the scientific collaboration and improve research productivity. [Methods] First, we established the scientific collaboration networks at individuals, institutions and regions levels. Then, we established a recommendation model based on network neighbors and paths. Finally, we conducted empirical study to examine the model at three levels. [Results] A total of 68 905 articles published from 2000 to 2014 on finance were analyzed to construct their research collaboration networks. The AUC values ??of the proposed model at individual, institutional and regional levels were 84.25%, 87.34%, and 91.84%, respectively, which were higher than those of the traditional algorithms. [Limitations] The training and testing sets were only classified by time. More segmentation methods were needed to optimize the new model. [Conclusions] This study helps researchers find collaboration opportunities, and provides new directions for studies on scientific collaboration networks.

Key wordsLink Prediction      Scientific Collaboration Recommendation      Scientific Collaboration Network      Multi-feature Fusion     
Received: 31 May 2017      Published: 28 September 2017
ZTFLH:  G350  

Cite this article:

Yu Chuanming,Gong Yutian,Zhao Xiaoli,An Lu. Collaboration Recommendation of Finance Research Based on Multi-feature Fusion. Data Analysis and Knowledge Discovery, 2017, 1(8): 39-47.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.08.05     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I8/39

个人层面 机构层面 区域层面
总集合 作者数: 4 123
合作链接数:
7 096
机构数: 3 383
合作链接数:
12 336
区域数: 46
合作链接数: 411
训练集 作者数: 4 049
合作链接数:
6 119
机构数: 3 289
合作链接数:
11 241
区域数: 46
合作链接数: 400
测试集 作者数: 1 080
合作链接数: 864
机构数: 1 109
合作链接数: 1 553
区域数: 36
合作链接数: 171
推荐 不推荐
有合作 TP FN
无合作 FP TN
编号 作者1 作者2
1 阎庆民 谢 平
2 陈卫东 姜波克
3 姜波克 张健华
4 阎庆民 陈卫东
5 阎庆民 张健华
6 温信祥 樊志刚
7 胡 浩 樊志刚
8 王佳佳 樊志刚
9 张燕生 唐 旭
10 胡 浩 马素红
编号 机构1 机构2
1 中国金融学会金融史专业委员会 上海市金融学会
2 烟台大学经管学院 东北财经大学公共管理学院
3 云南财经大学商学院 云南财经大学会计学院
4 云南大学国际关系研究院 南开大学日本研究院
5 复旦大学管理学院产业经济系 复旦大学管理学院财务金融系
6 东北财经大学应用金融学院 东北财经大学职业技术学院
7 西南大学地理科学学院 重庆大学建设管理与房地产学院
8 华东师范大学俄罗斯研究中心 华东师范大学国际关系与地区发展研究院
9 浙江大学理学院 浙江水利水电专科学校
10 中国科学技术大学公共事务学院 西南科技大学政治学院
编号 区域1 区域2
1 陕西 海南
2 河北 重庆
3 重庆 陕西
4 黑龙江 重庆
5 天津 广西
6 吉林 重庆
7 四川 辽宁
8 江苏 广西
9 贵州 天津
10 海南 江苏
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