ABSTRACT

Due to the failure of the existing systems to convert online service reputation evaluation, the accuracy, average recall rate and average comprehensive index of online service reputation evaluation show a straight-line downward trend. Therefore, this paper proposes an online service reputation system of agricultural products sales platform based on P2P network. This paper analyses the related concepts involved in the online service reputation system of agricultural products sales platform, designs the system under P2P network through B/S framework, mainly including the modules of online service reputation evaluation, information release and system account management. The online service reputation evaluation of agricultural products sales platform is transformed into service classification in multi-dimensional space. Machine learning is used to train the samples, and the optimal classifier model is established in multi-dimensional space to classify the online service of agricultural product sales platform, so as to achieve the final evaluation of online service reputation of agricultural product sales platform. The experimental results show that the accuracy and average recall rate of the system are close to 100%, and the average comprehensive index is up to 98.3%.

摘要

由于现有系统无法转换在线服务声誉评估，在线服务声誉评估的准确性，平均召回率和平均综合指数呈直线下降趋势。因此，本文提出了一种基于P2P网络的农产品销售平台在线服务信誉系统。本文分析了农产品销售平台在线服务信誉系统的相关概念，通过B / S框架设计了P2P网络下的系统，主要包括在线服务信誉评价，信息发布和系统账户管理等模块。将农产品销售平台的在线服务声誉评价转化为多维空间中的服务分类。通过机器学习对样本进行训练，在多维空间中建立最优的分类器模型，对农产品销售平台的在线服务进行分类，以达到对农产品销售平台在线服务声誉的最终评价。实验结果表明，该系统的准确性和平均召回率接近100％，平均综合指数高达98.3％。