• Korean Management Science Review
• /
• v.26 no.1
• /
• pp.183-196
• /
• 2009

Customer retention has been a pressing issue for companies to get and maintain the loyal customers in the competing environment. Lots of researchers make effort to seek the characteristics of the churning customers and the loyal customers using the data mining techniques such as decision tree. However, such existing researches don't consider relationships among customers. Social network analysis has been used to search relationships among social entities such as genetics network, traffic network, organization network and so on. In this study, a customer network is proposed to investigate the differences of network characteristics of churning customers and loyal customers. The customer networks are constructed by analyzing the real purchase data collected from a Korean cosmetic provider. We investigated whether the churning customers and the loyal customers have different degree centralities and densities of the customer networks. In addition, we compared products purchased by the churning customers and those by the loyal customers. Our data analysis results indicate that degree centrality and density of the churning customer network are higher than those of the loyal customer network, and the various products are purchased by churning customers rather than by the loyal customers. We expect that the suggested social network analysis is used to as a complementary analysis methodology with existing statistical analysis and data mining analysis.

• KNOM Review
• /
• v.23 no.1
• /
• pp.34-42
• /
• 2020

Network Function Virtualization (NFV) environment can deal with dynamic changes in traffic status with appropriate deployment and scaling of Virtualized Network Function (VNF). However, determining and applying the optimal VNF deployment is a complicated and difficult task. In particular, it is necessary to predict the situation at a future point because it takes for the process to be applied and the deployment decision to the actual NFV environment. In this paper, we randomly generate service requests in Multiaccess Edge Computing (MEC) topology, then obtain training data for machine learning model from an Integer Linear Programming (ILP) solution. We use the simulation data to train the machine learning model which predicts the optimal VNF deployment in a predefined future point. The prediction model shows the accuracy over 90% compared to the ILP solution in a 5-minute future time point.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.679-680
• /
• 2008

When we apply the neural networks to applications, we need to select proper architecture of the network and the activation function of the network is one of most important characteristics. In this research, we propose a method to make a network using multiple activation functions. The performance of the proposed method is investigated through the computer simulations on various regression problems.

• The Bulletin of The Korean Astronomical Society
• /
• v.34 no.1
• /
• pp.185.2-185.2
• /
• 2009

• Journal of Gifted/Talented Education
• /
• v.25 no.1
• /
• pp.21-36
• /
• 2015

The purpose of this study is to examine social influence of the counselors on the network for a career counseling on gifted students of science and general students. This study collected data from 151 gifted students of science and 212 general students. The collected data was analyzed by the social network analysis. The results are as follows: First, we found that mother had the highest centrality indicators and teacher had the lowest centrality indicators on the career counseling network in both groups. And the max-flow indicators from mothers to teachers were the lowest on the career counseling network, on other hand; general students had lower centrality indicators than gifted students of science. Second, father was the most obvious counselor to cover for mother, on the hand, teacher was the worst counselor to cover for mother on the career counseling network. The gifted students group of science had less difficulty to cover for mother than the general students group. While teacher had the highest limits to information exchange on the career counseling network in both groups, mother had the lowest limits. As the result, we can conclude that mother played a key role on the career counseling network in gifted students of science and general students, while teachers was excluded from the career counseling network of students. Therefore, it is necessary to connect systematically parents with teachers for leading effectively students to their career; also government needs to build a career counseling system for this.

• The Science & Technology
• /
• v.22 no.10 s.245
• /
• pp.81-83
• /
• 1989

• Journal of the Korean Data and Information Science Society
• /
• v.14 no.3
• /
• pp.715-723
• /
• 2003

A tandem network in which all nodes have the same load is considered. We derive bounds on the probability that the total population of the tandem network exceeds a large value by using its relation to the stationary distribution. These bounds imply a stronger asymptotic limit than that in the large deviation theory.

• 제어로봇시스템학회:학술대회논문집
• /
• 1989.10a
• /
• pp.1125-1128
• /
• 1989

In this paper, the inverse model of a servo system is realized in a PDP-type neural network. The neural network learns the mapping between the input and output of the servo system. Some simulation results show the effectiveness of this inverse model obtained here.

• Journal of the Korean Data and Information Science Society
• /
• v.16 no.4
• /
• pp.815-821
• /
• 2005

Among the various artificial neural networks the backpropagation network (BPN) has become a standard one. One of the components in a neural network is an activating function or a transfer function of which a representative function is a sigmoid. We have discovered that by updating the slope parameter of a sigmoid function simultaneous with the weights could improve performance of a BPN.

• Korean Management Science Review
• /
• v.11 no.1
• /
• pp.187-196
• /
• 1994

Time-Space-Time(T-S-T) switching network is modeled as a graceful degrading system. Call blocking probability is defined as a measure of performance. Several performance related measures are suggested under the presence of failure. An optimization model is proposed, which determines optimal values of system parameters of the switching network.