• Journal of Korea Society of Industrial Information Systems
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• v.9 no.3
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• pp.55-63
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• 2004

Most of current shooing malls on the internet do not satisfy all customers because they present arrangements of goods and suggestions uniformly and comprehensively according to the thinking of their managers. When classifying into groups according to generations, gender, income, job, hobby, etc. the propensity of purchase is showed differently and the interest and real purchasing power of the customer is different in shopping malls. This paper describes the development of customer oriented intelligent shopping mall system that is added not only statistical analysis dynamical activity of customers but also weight and construct optimal according to group of goods automatically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.169-174
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• 2002

According to the expansion of the E-Commerce based on Internet, the Interoperability between shopping malls and the expansibility of B2B has been needed. Also, Intelligent User Interface has been needed. The XML based Script Processor, the solution of the problem, is good for Interoperability and if a shopping mall is build by it, it is possible to do customer oriented display that an XML document is displayed with different looks by other style sheet according to customer's preference. In the proposed system, the TMP(Template Markup Language), an auto XML generation script, is defined by XML and the script processor is implemented to work on the shopping mall on the Web.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.366-370
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• 2003

In this research, we suggest a hybrid intelligent Web recommendation systems based on Web data mining and case-based reasoning (CBR). One of the important research topics in the field of Internet business is blending artificial intelligence (AI) techniques with knowledge discovering in database (KDD) or data mining (DM). Data mining is used as an efficient mechanism in reasoning for association knowledge between goods and customers＇ preference. In the field of data mining, the features, called attributes, are often selected primary for mining the association knowledge between related products. Therefore, most of researches, in the arena of Web data mining, used association rules extraction mechanism. However, association rules extraction mechanism has a potential limitation in flexibility of reasoning. If there are some goods, which were not retrieved by association rules-based reasoning, we can＇t present more information to customer. To overcome this limitation case, we combined CBR with Web data mining. CBR is one of the AI techniques and used in problems for which it is difficult to solve with logical (association) rules. A Web-log data gathered in real-world Web shopping mall was given to illustrate the quality of the proposed hybrid recommendation mechanism. This Web shopping mall deals with remote-controlled plastic models such as remote-controlled car, yacht, airplane, and helicopter. The experimental results showed that our hybrid recommendation mechanism could reflect both association knowledge and implicit human knowledge extracted from cases in Web databases.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.192-197
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• 2001

A recommendation system tracks past actions of a group of users to make a recommendation to individual members of the group. The computer-mediated marketing and commerce have grown rapidly nowadays so the concerns about various recommendation procedures are increasing. We introduce a recommendation methodology by which e-commerce sites suggest new products of services to their customers. The suggested methodology is based on web log analysis, product taxonomy, and association rule mining. A product recommendation system is developed based on our suggested methodology and applied to a Korean internet shopping mall. The validity of our recommendation system is discussed with the analysis of a real internet shopping mall case.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1387-1392
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• 2015

SCS(Social Curation Service) is a service system to help sale and consumption with intelligent information about consumer's favor which is got from the combination of social service and internet shopping mall. This paper develops and analyzes some algorithms for catching the customer's preference tendency in SCS system. The developed algorithms are implemented to verify it's efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.441-443
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• 2015

SCS(Social Curation Service)is a service system to help sale and consumption with intelligent information about consumer's favor which is got from the combination of social service and internet shopping mall. This paper develops and analyzes some algorithms for catching the customer's preference tendency in SCS system. The developed algorithms are implemented to verify it's efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.495-498
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• 2005

The study is aimed at searching algorithm upgrading which can automatically compose goods displayed according to the degree of popularity regarding customer's requests, for the purpose of design of an intellectual shopping mall on the net and putting it into force by using classified technical Data-mining and statical analysis including personal information , entrance records and purchase records. This is for the study of strategic marketing. The system can automate the conventional shopping mall system by manual and personal judgements and also suggest a new formation of marketing techniques to strengthen the competition in B2B market which is steeply increasing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.38-46
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• 2004

To be successful in increasingly competitive Internet marketplace, it is essential to capture customer loyalty. This paper deals with an intelligent agent approach to incorporate customer's sensibility into an one-to-one recommendation service in on-line shopping mall. In this paper the focus of interest is on-line recommendation service algorithm for development of Human Sensibility based web agent system. The recommendation agent system composed of seven services including specialized algorithm. The on-line recommendation service algorithm use human sensibility ergonomics and on-line preference matching technologies to tailor to the customer the suggestion of goods and the description of store catalog. Customizing the system's behavior requires the parallel execution of several tasks during the interaction (e.g., identifying the customer's emotional preference and dynamically generating the pages of the store catalog). Most of the present shopping malls go through the catalog of goods, but the future shopping malls will have the form of intelligent shopping malls by applying the on-line recommendation service algorithm.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.27-45
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• 2004

While on-line shopping is increasing, the "Consumer Protection Law in Electronic Commerce" obliges each internet shopping mall to provide its business information. Although most internet shopping malls provide their business information in the semi-structured format on the bottom of their homepages, the attributes and expression forms of business information are different each other. It makes consumers difficult to identify their business information and lowers public confidence. Hence this study proposes three approaches - HTML-based structure, XML-based structure, and XML data island-based structure - to structuralizing business information for correct expression. The experiment results showed that the business information extraction time by XML data island-based structure is independent of the size of the web document, while the time by HTML-based structure is dependent on the size. By comparing the business information extraction times, we show that XML data island-based structure is more efficient and effective than HTML-based structure.structure.

• Journal of Intelligence and Information Systems
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• v.15 no.3
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• pp.81-102
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• 2009

In this study, we investigated how to achieve differentiation for the ISM (Internet Shopping Mall) to improve profitability, which is required for survival in the fiercely competitive ISM industry. We analyzed implementation level key managerial factors that could contribute to the differentiation of the ISM. The research model is constructed through integration of two distinctive research streams of e-commerce. The one is B2C differentiation strategy research, most of which are conceptual and conducted at a strategy level, and the other is empirical research analyzing the antecedents of customer satisfaction at the ISM. This study is organized as follows. First, we draw upon transaction cost theory to organize constructs representing customer value associated with the customer buying decision process. Next, after reviewing comprehensive managerial factors that could impact on customer value, we selected 15 managerial factors that could contribute to the differentiation of the ISM to deliver value to customers. Finally, the resulting structural model is validated through empirical analyses. The results provide insights for future studies on ISM differentiation.