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Research on MIL Search Method for P2P Borrowing Loss Clients Based on Social Network Perspective

机译:基于社交网络视角的P2P借贷客户MIL搜索方法研究

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This paper proposes a multi-indicator search study based on the social network perspective for borrowing and lending customers. When studying P2P lending and losing customers, according to the division of interpersonal relationship in sociology and the extent to which the client can be debited in reality, it is divided into three kinds of relationship networks: blood relationship network, geo-relationship network and business relationship network, assisting to combine the two-mode subordinate network of the lost customers, and focusing on analyzing its scale, density and other indicators, and hope to find the target lost customers. Key figures in the social network of interpersonal relationships, message communicators, behavioral influencers, etc., to achieve the search for lending customers after their sudden loss. For the first time, this paper applies the social network theory to the search for borrowed and lost customers and proposes the MIL algorithm. It proposes a new idea for the hiddenness of the loan client’s loss of connection, and accelerates the governance of the ill-fated phenomenon of loan and loan loss effectiveness. This paper also analyzes the case and proposes relevant suggestions in connection with a loss event in Guangzhou.
机译:本文提出了一种基于社会网络视角的借贷客户多指标搜索研究。在研究P2P借贷和丢失客户时,根据人际关系在社会学上的划分以及客户实际可借记的程度,将其分为三种关系网络:血液关系网络,地理关系网络和业务关系网络,协助将流失客户的双模下属网络进行合并,并重点分析其规模,密度等指标,并希望找到目标流失客户。人际关系,消息沟通者,行为影响者等社交网络中的关键人物,可以在突然失去客户之后寻找借贷客户。本文首次将社会网络理论应用于寻找借入和丢失的客户,并提出了MIL算法。它为隐藏贷款客户失去联系的可能性提出了新的思路,并加快了对不良贷款现象和贷款损失有效性的治理。本文还对案件进行了分析,并针对广州的一次损失事件提出了相关建议。

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