• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.250-257
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• 2002

Clustering is a data mining method, which consists in discovering interesting data distributions in very large databases. In traditional data clustering, similarity of a cluster of object is measured by pairwise similarity of objects in that paper. In view of the nature of clustering transactions, we devise in this paper a novel measurement called item similarity and utilize this to perform clustering. With this item similarity measurement, we develop an efficient clustering algorithm for target marketing in each group.

• Journal of the Korea Computer Industry Society
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• v.2 no.9
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• pp.1175-1182
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• 2001

One to one Marketing (a.k.a. database marketing or relationship marketing) is one of the many fields that will benefit from the electronic revolution and shifts in consumer sales and advertising. As a component of intelligent customer services on Internet storefront, this paper describes technology of providing personalized advertisement using the market basket analysis, a well-Known data mining technique. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customer's data. However, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed Knowledge base. In this paper, using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.99-104
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• 2016

This paper aims to develop the One-In-One web solutions that can work in PC, tablet, notebook, and smart phone depending on the flow of the ICT times to promote the marketing of the technology. The characteristics of this web solutions can be used to a image viewer system of 3D array type for PC, tablet, notebook, and smart phone. It is implemented in the design of 3D display slide show type. And it is developed an image viewer system, which enables users to use by utilizing the links manner ICT base required by each channel of the image. This is the 3D photo viewer PR solution developed in the way that anyone can use easily without the knowledge of programming in various areas such as public relations, business, and education.

• Journal of Information Technology Services
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• v.11 no.2
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• pp.229-242
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• 2012

The MICE(Meeting, Incentive travel, Convention, and Exhibition) industry grows steadily. Especially, exhibition industry plays an important role as the effective sales and marketing tools. However, lots of studies have focused on the flow analysis of audience traffic, booth recommendation or formulaic interactions between audiences and contents in the exhibition hall. In this study, we proposed an intelligent Interactive system considering audience's response for providing personalized exhibition service. First, we extracted components of the system architecture through the previous studies. Second, we suggested the system architecture and scenarios for intelligent interactions between audiences and contents. We hope that the proposed system will strengthen the basis for implementing interactive system in the exhibition industry.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.125-133
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• 1999

The objective of knowledge discovery and data mining lies in the generation of useful insights from a store of data. This paper presents a framework for knowledge mining to provide a systematic approach to the selection and deployment of tools for automated learning. Every methodology has its strengths and limitations. Consequently, a multistrategy approach may be required to take advantage of the strengths of disparate technique while circumventing their individual limitations. For concreteness, the general framework for data mining in marketing is examined in the context of developing agents for optimizing a supply chain network.

• Journal of East Asia Management
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• v.1 no.1
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• pp.65-87
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• 2020

In recent years, with the rapid development of network live streaming, with the popularization of mobile Internet and mobile terminal equipment, the live streaming industry has ushered in great development. A sudden outbreak of the COVID-19 makes the PC end live streaming which has been developed for many years enter a new era, giving birth to the rapid development of mobile end live streaming. Not only because of the expansion of the live streaming industry market, the rise of the trend of the national live streaming, but also because the mobile live streaming is more and more valued by the brand, becoming an important tool for brand communication and product promotion. It is because of its unique communication characteristics that some scholars believe that the era of precision marketing has been opened by live network. Mobile live from the initial fans to reward and promote the brand, to now in the form of live marketing, consumers can "buy while watching". The time period from the understanding of the goods to the final completion of the purchase behavior has been greatly shortened. It is conducive to improving sales volume and brand awareness. Marketing communication through mobile live platform has become a popular way of brand marketing. This paper mainly studies the current situation, methods, problems and development strategies of brand marketing activities with the help of live streaming platform under the background of mobile internet. Taking Tmall live streaming platform as an example, this paper analyzes several ways of brand marketing with the help of live streaming and some universal characteristics of live streaming marketing by using the relevant theories of marketing. In view of the problems existing in live streaming brand marketing, it puts forward relevant Improvement measures. First of all, the paper puts forward the innovation in content and form. Second, the paper suggests that we should make full use of new technologies such as AR and VR to effectively combine with mobile live broadcasting. Third, the paper explores the integration of multiple channels to create intelligent marketing, and further optimize the live interface of mobile terminals. Finally, the paper emphasizes that the government departments and the platform itself should jointly supervise the mobile network live streaming platform and establish a good live broadcasting environment for mobile terminals. With the help of mobile live streaming, the marketing mode has an important impact on the promotion of brand marketing. How to make better use of this business mode and accurately use mobile live broadcast to promote brand marketing, so that enterprises can create greater profits, is also of profound research significance.

• Korean Management Science Review
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• v.21 no.3
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• pp.101-113
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• 2004

In the rapidly propagating Internet based electronic transaction environment. the importance of real time order confirmation has been more emphasized, In this paper, using data mining techniques, we develop intelligent operations decision model to allow real time order confirmation at the time the customer places an order with required delivery terms. Among various operation plannings used for order fulfillment. mill routing is the first interface decision point to link the order receiving at the marketing with the production planning for order fulfillment. Though linear programming based mathematical optimization techniques are mostly used for mill routing problems, some early orders should wait until sufficient orders are gathered for optimization. And that could effect longer order fulfillment lead-time, and prevent instant order confirmation of delivery terms. To cope with this problem, we provide the intelligent decision model to allow instant order based mill routing decisions. Data mining techniques of decision trees and neural networks. which are more popular in marketing and financial applications, are used to develop the model. Through diverse computational trials with the industrial data from the steel company. we have reported that the performance of the proposed approach is effective compared to the present heuristic only mill routing results. Various issues of data mining techniques application to the mill routing problems having linear programming characteristics are also discussed.

• Asia pacific journal of information systems
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• v.25 no.1
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• pp.83-97
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• 2015

Recently, the exhibition industry has developed rapidly with the development of information technologies. Most exhibitors in an exhibition plan and deploy many events that may provide advantages to visitors as a method of effective promotion. The growth and propagation of wireless technologies is a powerful marketing tool for exhibitors. However, exhibitors still rely on domain experts who are costly and time consuming because of the manual knowledge input procedure. Moreover, it is prone to biases and errors and not suitable for managing fast-growing and tremendous amounts of data that far exceed a human's ability to comprehend. To overcome these problems, data mining technology may be a great alternative, but it needs to be fit to each exhibition. This study uses data mining technology with the Predictive Model Markup Language (PMML) to suggest a system that supports intelligent services and that improves stakeholder satisfaction. This system provides advantages to the exhibitor, show organizer, and system designer, and is first enhanced by integrating data mining technologies through the knowledge of exhibition experts. Second, using the PMML, the system can automate the process of applying data mining models to solve real-time processing problems in the exhibition environment.

• The Research Journal of the Costume Culture
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• v.26 no.6
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• pp.872-887
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• 2018

This study aims to identify the differences between Korean and Chinese and males and females in terms of female image preferences. The survey was conducted for 1 month targeting male and female Korean and Chinese subjects. Among the 350 completed questionnaires, 309 were used for analysis. For the analysis, 11 female images were chosen based on theoretical study, then a t-test and a paired t-test were carried out using SPSS 19.0. The results of this study are as follows: First, differences in female image preferences were observed to depend on nationality and gender. Koreans prefer urban images while Chinese prefer cute, intelligent, and sexy images. Second, males prefer innocent or sexy images, while females prefer sophisticated images. Third, Korean males prefer innocent, active, sophisticated, gentle, cute, sexy, urban, natural, intelligent, spectacular, and neutral images in order. Chinese males prefer gentle, innocent, sexy, active, sophisticated, intelligent, cute, natural, urban, spectacular, and neutral images in order. Fourth, Korean females prefer sophisticated, gentle, urban, natural, intelligent, innocent, active, sexy, cute, spectacular, and neutral images in order. Chines females prefer sophisticated, intelligent, cute, gentle, innocent, active, natural, sexy, urban, spectacular, and neutral images in order. Using these results, it will be possible to design marketing strategies for global consumers.

• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.179-193
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• 2003

Clustering is a data mining method which help discovering interesting data groups in large databases. In traditional data clustering, similarity between objects in the cluster is measured by pairwise similarity of objects. But we devise an advanced measurement called item similarity in this paper, in terms of nature of clustering transaction data and use this measurement to perform clustering. This new algorithm show the similarity by accepting the concept of relationship between different attributes. With this item similarity measurement, we develop an efficient clustering algorithm for target marketing in each group.