• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.361-371
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• 1999

This paper is concerned with designing and implementing the Internet shopping mall by using virtual reality-driven avatar and web decision support system. Traditionally, the Internet shopping mall has been designed based on the combination of several hyperlinks, images, and texts. However, this sort of approach results in a lower performance because possible customers cannot make more accurate shopping decisions. To overcome this kind of pitfalls facing the current Internet shopping malls, we propose using a combination of virtual reality and web DSS. The main virtues of our proposed approach to designing the Internet shopping mall are as follows: First, the virtual reality technique is emerging as one of alternative guaranteeing a sense of reality for customers part and facilitating the complex process of shopping decision makings. Especially, the avatar, which is an artificially designed man working on the Internet, can make easy and absorbing the Internet shopping-related decision making processes. Second, the web DSS approach can provide an effective decision support mechanism for customers. Especially, we design a set of intelligent agents for the proposed web DSS. Experimental results with an illustrative example showed that our proposed approach can yield a new Internet shopping mall paradigm with which customers can benefit from a high level of decision support functions.

• Journal of Internet Computing and Services
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• v.2 no.1
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• pp.63-75
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• 2001

With the popularization of internet, its application fields are spreading out every industry parts, especially there are great change in marketing areas by the internet. One of them is shopping mall. Assembly PC of old method being sale shopping mall is not consider in compatibility of each devices, because of using the assembling method of it. In this paper, in order to their has not specific knowledge on computer and consider of a compatibility to each devices, our implemented shopping mall that on the provided convenience by using the on-line customer, M implemented intelligent agent can advise compatibility of each devices using Fuzzy value.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.361-371
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• 1999

This paper is concerned with designing and implementing the Internet shopping mall by using virtual reality-driven avatar and web decision support system. Traditionally, the Internet shopping mall has been designed based on the combination of several hyperlinks, images, and tents. However, this sort of approach results in a lower performance because possible customers cannot make more accurate shopping decisions. To overcome this kind of pitfalls facing the current Internet shopping malls, we propose using a combination of virtual reality and web DSS. The main virtues of our proposed approach to designing the Internet shopping mall are as follows: First, the virtual reality technique is emerging as one of alternatives guaranteeing a sense of reality for customers' part and facilitating the complex process of shopping decision makings. Especially, the avatar, which is an artificially designed man working on the Internet, can make easy and absorbing the Internet shopping-related decision making processes. Second, the web DSS approach can provide an effective decision support mechanism for customers. Especially, we design a set of intelligent agents for the proposed web DSS. Experimental results with an illustrative example showed that our proposed approach can yield a new Internet shopping mall paradigm with which customers can benefit from a high level of decision support functions.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.456-463
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• 2001

Understanding and adapting to changes of customer behavior in internet shopping mall is an important aspect to survive in continuously changing environment. This paper develops a methodology based on decision tree algorithms to detect changes of customer behavior automatically from customer profiles and sales data at different time snapshots. We first define three types of changes as emerging pattern, unexpected change and the added/perished rule. Then, it is developed similarity and difference measures for rule matching to detect all types of change. Finally, the degree of change is developed to evaluate the amount of change. A Korean internet shopping mall case is evaluated to represent the performance of our methodology. And practical business implications for this methodology are also provided.

• Asia pacific journal of information systems
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• v.9 no.4
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• pp.107-124
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• 1999

This paper describes a personalized advertisement technique as a part of intelligent customer services in Internet shopping malls. Based on customers' initial profile, purchase history, and behaviors in an Internet shopping mall, the technique displays appropriate advertisements on Internet web pages when customers' visit to the shopping mall. Customers preference scores for product groups which are main sources to select advertisements, are stored either a preference table or preference trees. Both of the two storage methods can support selection of advertisements on real time, and the preference tree method can reflect affinity among product groups. The suggested technique selects different advertisements to reflect changes of customers preferences as time goes by. An experiment has been performed to evaluate the effectiveness of the algorithm, which revealed that the algorithm selects more customer-oriented advertisements rather than random selection.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.33-51
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• 1999

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.153-177
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• 2001

Nowadays, product recommendation is one of the important issues regarding both CRM and Internet shopping mall. Generally, 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 and thereby automatic recommendation methodologies have got great attentions. But the researches and commercial tools for product recommendation so far, still have many aspects that merit further considerations. To supplement those aspects, we devise a recommendation methodology by which we can get further recommendation effectiveness when applied to Internet shopping mall. The suggested methodology is based on web log information, product taxonomy, association rule mining, and decision tree learning. To implement this we also design and intelligent Internet shopping mall support system based on agent technology and develop it as a prototype system. We applied this methodology and the prototype system to a leading Korean Internet shopping mall and provide some experimental results. Through the experiment, we found that the suggested methodology can perform recommendation tasks both effectively and efficiently in real world problems. Its systematic validity issues are also discussed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.342-351
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• 2002

A personalized product recommendation is an enabling mechanism to overcome information overload occurred when shopping in an Internet marketplace. Collaborative filtering has been known to be one of the most successful recommendation methods, but its application to e-commerce has exposed well-known limitations such as sparsity and scalability, which would lead to poor recommendations. This paper suggests a personalized recommendation methodology by which we are able to get further effectiveness and quality of recommendations when applied to an Internet shopping mall. The suggested methodology is based on a variety of data mining techniques such as web usage mining, decision tree induction, association rule mining and the product taxonomy. For the evaluation of the methodology, we implement a recommender system using intelligent agent and data warehousing technologies.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.183-190
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• 2009

The core technique of ubiquitous computing is the context aware computing and the context aware technique is more like software so the important research work is to develop the core engines first and the adapted device for the engines. When ubiquitous computing era comes, the current existing internet shopping mall, the form of searching the direct goods and ordering the goods by the customers evolves and develops the form of system that recommends the goods by the search engine which combined with the input data and technique of case based reasoning and intelligent agent that is based on the context aware technique. In this paper, search engine which is based on the case based reasoning and intelligent agent is designed and the prototype is implemented to be adapted to the internet fashion expert shopping mall.

• Asia pacific journal of information systems
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• v.12 no.3
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• pp.71-88
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• 2002

In this paper, intelligent marketing and merchandising methods utilizing data mining and Web mining techniques are proposed for online retailers to survive and succeed in gaining competitive advantage in a highly competitive environment. The first part of this paper explains the procedures of one-to-one marketing based on customer relationship management(CRM) techniques and personalized recommendation lists generation. The second part illustrates Web merchandising methods utilizing data mining techniques, such as association and sequential pattern mining. We expect that our Web marketing and merchandising methods will both provide a currently operating Internet shopping mall with more selling opportunities and give more useful product information to customers.