Research on Protecting Information Security Based on the Method of Hierarchical Classification in the Era of Big Data

Big data is becoming increasingly important because of the enormous information generation and storage in recent years.It has become a challenge to the data mining technique and management.Based on the characteristics of geometric explosion of information in the era of big data,this paper studies the possible approaches to balance the maximum value and privacy of information,and disposes the Nine-Cells information matrix,hierarchical classification.Furthermore,the paper uses the rough sets theory to proceed from the two dimensions of value and privacy,establishes information classification method,puts forward the countermeasures for information security.Taking spam messages for example,the massive spam messages can be classified,and then targeted hierarchical management strategy was put forward.This paper proposes personal Information index system,Information management platform and possible solutions to protect information security and utilize information value in the age of big data.

Bifurcation and optimal control for an infectious disease model with the impact of information

A nonlinear infectious disease model with information-influenced vaccination behavior and contact patterns is proposed in this paper,and the impact of information related to disease prevalence on increasing vaccination coverage and reducing disease incidence during the outbreak is considered.First,we perform the analysis for the existence of equilibria and the stability properties of the proposed model.In particular,the geometric approach is used to obtain the sufficient condition which guarantees the global asymptotic stability of the unique endemic equilibrium Ee when the basic reproduction number Ro>1.Second,mathematical derivation combined with numerical simulation shows the existence of the double Hopf bifurcation around Ee.Third,based on the numerical results,it is shown that the information coverage and the average information delay may lead to more complex dynamical behaviors.Finally,the optimal control problem is established with information-infuenced vaccination and treatment as control variables.The corresponding optimal paths are obtained analytically by using Pontryagin's maximum principle,and the applicability and validity of virous intervention strategies for the proposed controls are presented by numerical experiments.

Early Warning and Monitoring of Coronavirus Disease 2019 Using Baidu Search Index and Baidu Information Index in Guangxi,China

Coronavirus disease 2019(COVID-19)is an emerging infectious disease,and it is important to detect early and monitor the disease trend for policymakers to make informed decisions.We explored the predictive utility of Baidu Search Index and Baidu Information Index for early warning of COVID-19 and identified search keywords for further monitoring of epidemic trends in Guangxi.A time-series analysis and Spearman correlation between the daily number of cases and both the Baidu Search Index and Baidu Information Index were performed for seven keywords related to COVID-19 from January 8 to March 9,2020.The time series showed that the temporal distributions of the search terms“coronavirus,”“pneumonia”and“mask”in the Baidu Search Index were consistent and had 2 to 3 days'lead time to the reported cases;the correlation coefficients were higher than 0.81.The Baidu Search Index volume in 14 prefectures of Guangxi was closely related with the number of reported cases;it was not associated with the local GDP.The Baidu Information Index search terms“coronavirus”and“pneumonia”were used as frequently as 192,405.0 and 110,488.6 per million population,respectively,and they were also significantly associated with the number of reported cases(rs>0.6),but they fluctuated more than for the Baidu Search Index and had 0 to 14 days'lag time to the reported cases.The Baidu Search Index with search terms“coronavirus,”“pneumonia”and“mask”can be used for early warning and monitoring of the epidemic trend of COVID-19 in Guangxi,with 2 to 3 days'lead time.

Supervised non-negative matrix factorization based latent semantic image indexing

A novel latent semantic indexing （LSI） approach for content-based image retrieval is presented in this paper. Firstly, an extension of non-negative matrix factorization （NMF） to supervised initialization is discussed. Then, supervised NMF is used in LSI to find the relationships between low-level features and high-level semantics. The retrieved results are compared with other approaches and a good performance is obtained.

Analyzing the Potential Influence of Shanghai Stock Market Based on Link Prediction Method

In this paper, we analyze the 180 stocks which have the potential influence on the Shanghai Stock Exchange(SSE). First, we use the stock closing prices from January 1, 2005 to June 19, 2015 to calculate logarithmic the correlation coefficient and then build the stock market model by threshold method. Secondly, according to different networks under different thresholds, we find out the potential influence stocks on the basis of local structural centrality. Finally, by comparing the accuracy of similarity index of the local information and path in the link prediction method, we demonstrate that there are best similarity index to predict the probability for nodes connection in the different stock networks.