习客:走向现代教育的网络化学习型组织

"习客"(seeker)--网络环境下的主动学习者及学习型组织."习客"主题学习网站给自己的定位--不仅是学生学习的"习客",更是教师发展的"习客".

Application of a cost-sensitive method for churn prediction in telecommunication industry

To deal with the data mining problem of asymmetry misclassification cost, an innovative churn prediction method is proposed based on existing churn prediction research. This method adjusts the misclassification cost based on the C4. 5 decision tree as a baseline classifier, which can obtain the prediction model with a minimum error rate based on the assumption that all misclassifications have the same cost, to realize cost-sensitive learning. Results from customer data of a certain Chinese telecommunication company and the fact that the churners and the non-churners have different misclassification costs demonstrate that by altering the sampling ratio of churners and non-churners, this cost-sensitive learning method can considerably reduce the total misclassification cost produced by traditional classification methods. This method can also play an important role in promoting core competence of Chinese telecommunication industry.

软件

SAP公司和INFORMIX公司日前宣布将继续合作,致力于为INFORMIX动态服务器开发一种SAP商业信息仓库(BIW)。这个联合开发的数据仓库解决方案有望于今年晚些时候出台。两家公司同时宣布推出共同开发的高级数据库管理工具SAPDBA,该工具能迅速灵活地管理基于INFORMIX的SAP R/3系统,从而使客户总体拥有成本更加低廉。SAPDBA for

Probabilistic interval prediction of metro-to-bus transfer passenger flow in the trip chain

To accurately analyze the fluctuation range of time-varying differences in metro-to-bus transfer passenger flows,the application of a probabilistic interval prediction model is proposed to predict transfer passenger flows.First,bus and metro data are processed and matched by association to construct the basis for public transport trip chain extraction.Second,a reasonable matching threshold method to discriminate the transfer relationship is used to extract the public transport trip chain,and the basic characteristics of the trip based on the trip chain are analyzed to obtain the metro-to-bus transfer passenger flow.Third,to address the problem of low accuracy of point prediction,the DeepAR model is proposed to conduct interval prediction,where the input is the interchange passenger flow,the output is the predicted median and interval of passenger flow,and the prediction scenarios are weekday,non-workday,and weekday morning and evening peaks.Fourth,to reduce the prediction error,a combined particle swarm optimization(PSO)-DeepAR model is constructed using the PSO to optimize the DeepAR model.Finally,data from the Beijing Xizhimen subway station are used for validation,and results show that the PSO-DeepAR model has high prediction accuracy,with a 90%confidence interval coverage of up to 93.6%.

The research of Chinese Government Public Relations-- Based on the idea of the Balanced Scorecard

Through analyzing the problems of Chinese government public relations, using the idea of the Balanced Scorecard, we analyze the reasons of these problems and discuss the countermeasures from four aspects that conclude financial, internal operations, customers, learning and growth to achieve the all-round and balanced development of public relations and establish a high level of government public relations organization, regarding the overall strategic goal of government public relations that aim to strengthen the communication with various public, establish an innovative, pragmatic, honest and efficient government image in the public and the international community as the center.

Study on the Factors Driving the Loyalty of the Customers of a Third Party Mobile Payment Platform

. In this paper, the main driving factors affecting the customer loyalty of a third party mobile payment service were chosen by combining with the actual situation of the third party mobile payment service and customer spending habits in China. The assumed relations between all affecting factors and the customer loyalty of a third party mobile payment platform were proposed, and a model for studying customer loyalty was established and also a conclusion was made through the questionnaire survey analysis data. Finally, suggestions on improving the loyalty of the customers of a third party mobile payment platform are presented.

Distributed secure quantum machine learning

Distributed secure quantum machine learning （DSQML） enables a classical client with little quantum technology to delegate a remote quantum machine learning to the quantum server with the privacy data preserved. Moreover, DSQML can be extended to a more general case that the client does not have enough data, and resorts both the remote quantum server and remote databases to perform the secure machi~ learning. Here we propose a DSQML protocol that the client can classify two-dimensional vectors to dif- ferent clusters, resorting to a remote small-scale photon quantum computation processor. The protocol is secure without leaking any relevant information to the Eve. Any eavesdropper who attempts to intercept and disturb the learning process can be noticed. In principle, this protocol can be used to classify high dimensional vectors and may provide a new viewpoint and application for future ＂big data＂.