基于人群智能交易网络的交易信用管理机制

Zhishuo Liu, Nianci Kou, Zhuonan Han, Ziqi Dong, Dongxin Yao
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引用次数: 0

摘要

目前已有研究提出了基于平台的电子商务信用管理技术。电子商务系统交易信用的最新研究提出了直接信用和推荐两种信用,并据此构建了基于人群智能的交易网络模型。然而,交易信用模型是否高效有序,不仅取决于模型本身,还取决于交易信用管理机制。因此,本文针对基于人群智能交易网络的特点,对交易信用管理机制进行了深入研究,提出了“买家+朋友圈”的交易信用数据存储和更新方法,构建了基于广度和深度搜索算法相结合的信用数据搜索方法。“买家+朋友圈”的方式不仅可以充分利用互联网的计算和存储能力,而且可以解决单节点故障的问题。该算法对查询请求的转发策略进行优化。此外,仿真结果表明,该算法可以更快地获取更多的目标资源,并能有效地减少网络中的冗余消息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Transaction Credit Managing Mechanism Based on the Crowd Intelligence-Based Transaction Network
Current studies have proposed the platform-based e-commerce credit management technology. The latest research of transaction credit of e-commerce system proposes two kinds of credit, which is direct credit and recommends, and accordingly constructs a model for the transaction network based on crowd intelligence. However, whether the transaction credit model is efficient and orderly or not depends not only on the model itself, but also on the transaction credit managing mechanism. Therefore, this paper carries out in-depth research on the transaction credit managing mechanism based on characteristics of the crowd intelligence-based transaction network, and proposes the method of "buyer + circle of friends" for transaction credit data storing and updating, and builds a credit data searching method based on the combination of breadth and depth search algorithm. The "buyer +circle of friends" method not only can make full use of the computing and storing ability of the internet, but also can solve the problem of single node failure. The algorithm optimizes the forwarding strategy of the query request. In addition, the simulation results show that the algorithm can acquire more target resources faster and can effectively reduce the amount of redundant messages in the network.
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