Decision Model of Knowledge Transfer in Big Data Environment  

作　　者：Chuanrong Wu Yingwu Chen Feng Li 

机构地区：[1]Changsha University of Science&Technology,Changsha,China [2]National University of Defense Technology,Changsha,China

出　　处：《China Communications》2016年第7期100-107,共8页中国通信（英文版）

基　　金：supported by NSFC(Grant No.71373032);the Natural Science Foundation of Hunan Province(Grant No.12JJ4073);the Scientific Research Fund of Hunan Provincial Education Department(Grant No.11C0029);the Educational Economy and Financial Research Base of Hunan Province(Grant No.13JCJA2);the Project of China Scholarship Council for Overseas Studies(201208430233;201508430121)

摘　　要：A decision model of knowledge transfer is presented on the basis of the characteristics of knowledge transfer in a big data environment.This model can determine the weight of knowledge transferred from another enterprise or from a big data provider.Numerous simulation experiments are implemented to test the efficiency of the optimization model.Simulation experiment results show that when increasing the weight of knowledge from big data knowledge provider,the total discount expectation of profits will increase,and the transfer cost will be reduced.The calculated results are in accordance with the actual economic situation.The optimization model can provide useful decision support for enterprises in a big data environment.A decision model of knowledge transfer is presented on the basis of the characteristics of knowledge transfer in a big data environment.This model can determine the weight of knowledge transferred from another enterprise or from a big data provider.Numerous simulation experiments are implemented to test the efficiency of the optimization model.Simulation experiment results show that when increasing the weight of knowledge from big data knowledge provider,the total discount expectation of profits will increase,and the transfer cost will be reduced.The calculated results are in accordance with the actual economic situation.The optimization model can provide useful decision support for enterprises in a big data environment.

关 键 词：big data knowledge transfer optimization simulation dynamic network 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] TU982[自动化与计算机技术—计算机科学与技术]