• The KIPS Transactions:PartD
• /
• v.11D no.5
• /
• pp.1205-1212
• /
• 2004

As electronic commerce systems have been widely used, the necessity of adaptive e-commerce agent systems has been increased. These kinds of adaptive e-commerce agents can monitor customer's behaviors and cluster thou in similar categories, and include user's preference from each category. In order to implement our adaptive e-commerce agent system, in this paper, we propose an adaptive e-commerce agent systems consider customer's information of interest and goodwill ratio about preference goods. Proposed system build user's profile more accurately to get adaptability for user's behavior of buying and provide useful product information without inefficient searching based on such user's profile. The proposed system composed with three parts , Monitor Agent which grasps user's intension using monitoring, similarity reference Agent which refers to similar group of behavior pattern after teamed behavior pattern of user, Interest Analyzing Agent which personalized behavior DB as a change of user's behavior.

• The KIPS Transactions:PartB
• /
• v.9B no.6
• /
• pp.775-782
• /
• 2002

As electronic commerce systems have been widely used, the necessity of adaptive e-commerce agent systems has been increased. These kinds of agents can monitor customer's purchasing behaviors, clutter them in similar categories, and induce customer's preference from each category. In order to implement our adaptive e-commerce agent system, we focus on following 3 components-the monitor agent which can monitor customer's browsing/purchasing data and abstract them, the conceptual cluster agent which cluster customer's abstract data, and the customer profile agent which generate profile from cluster, In order to infer more accurate customer's preference, we propose a 2 layered structure consisting of conceptual cluster and inductive profile generator. Many systems have been suffered from errors in deriving user profiles by using a single structure. However, our proposed 2 layered structure enables us to improve the qualify of user profile by clustering user purchasing behavior in advance. This approach enables us to build more user adaptive e-commerce system according to user purchasing behavior.

• The KIPS Transactions:PartC
• /
• v.8C no.6
• /
• pp.855-864
• /
• 2001

With the increasing importance and complexity of EC (Electronic Commerce) across the Internet, the need and expectation for intelligent software agents to support both consumers and suppliers through the whole process of EC are growing rapidly. To realize the intelligent EC. a multiagent based EC system. which includes foundational technologies such as the establishment of standard product ontology the definition of message and negotiation protocol and brockering, is required. In this paper we propose an intelligent EC System named ICOMA(Intelligent electronic CO mmerce system based on Multi-Agent) as an open infrastructure of multiagent-based EC. Concretely we have proposed. designed and implemented an architecture of multiagent-based EC system including 6-types of agents message protocol for inter-agent negotiation, personalized produst retrieval and filtering., We have confirmed the effectiveness of the system through experiments.

• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10b
• /
• pp.90-92
• /
• 1999

최근 전자상거래를 위해 개발되는 대부분의 쇼핑에이전트들은 고객의 선호도를 고려하지 않은 일차원적인 비교, 예를 들어 가격비교 기능만을 가지고 있다. 이러한 일차원적 비교는 다양한 상품 특성을 고려할 수가 없다. 고객이 상품을 구매할 때 만족을 얻지 못하는 것은 그들이 서로 다른 성향을 가지고 있기 때문이다. 따라서 고객에게 가치 있는 상품 정보를 제공할 수 있는 지능형 쇼핑에이전트의 개발이 전자상거래에서 요구된다. 본 논문에서 우리는 다차원 비교쇼핑을 지원하는 지능형 쇼핑에이전트를 제안한다. 이것은 다양한 고객 선호도에 따른 고객의 요구에 부합되도록 한다. 고객의 선호도를 예측하기 위해서 쇼핑에이전트는 고객으로부터의 피드백과 트랜잭션 정보를 분석한다. 그리고 다음 구매를 위해 고객 선호도를 재 산정한다. 이러한 지능형 쇼핑에이전트는 고객 선호도의 변화에 능동적으로 적응해야 한다. 본 연구의 대상 상품은 책이다. 본 논문에서 제안하는 쇼핑에이전트는 서로 다른 선호도를 가진 각각의 고객에 대해서 유용한 결과를 보인다. 이러한 실험을 통해 우리는 고객 선호도의 변화를 확인할 수 있다.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.5S
• /
• pp.1696-1707
• /
• 2000

With the proliferation of electronic commerce (EC), the product items which are transacted and the user classes who utilize the EC are spread rapidly. Many users have to expend time and effort in searching of products an or the shopping malls which deal with the products. For his reason, the intelligent retrieval of both malls and products based on an intelligent software agent has been raised as a hot issue. In this paper we have constructed an ontology server that is an essential constituent for agent-based intelligent EC. And also we have designed and implemented a use adapted personalized product search function based on the ontology that are registered in the server.

• The Journal of the Korea Contents Association
• /
• v.1 no.1
• /
• pp.51-58
• /
• 2001

Electronic commerce system must provide convenient interface, easy and fast searching function, and production information satisfying customers. To do this, many kinds of studies are being advanced actively about electronic commerce system using intelligent agent electronic This paper suggests 2-tier electronic commerce system using intelligent multi agent. We propose a combined reasoning agent system which provides production information satisfying customer's needs using both case-based reasoning and rule-based reasoning. And this system distribute network and sewer system load based on load balancing and 2-tier agent structure. This system can find production information through teaming of rule-based reasoning method and case-based reasoning method. This system can provide the best suitable production information to customers by using combined reasoning agent system. And we can prevent customer's unexpected long waiting causes by network traffic and server load.

• Proceedings of the Korean Information Science Society Conference
• /
• 2001.04b
• /
• pp.343-345
• /
• 2001

전자상거래 시장의 규모 및 상점 수의 증가로 인하여 상품 구매자의 상품 구입을 보조해 줄 수 있는 에이전트 기술의 필요성이 증가하고 있다. 본 논문에서는 전자상거래에서 사용자의 선호도를 반영하여 상품을 추천해주는 지능형 에이전트 모델을 제안한다. 상품 정보 및 사용자의 선호도 정보를 관리하기 위하여 계층적 퍼지 그래프를 이용함으로써, 제안된 모델은 기존에 비해 더 나은 융통성과 효율성을 보일 수 있다. 에이전트에 의한 추천 상품은 사용자 선호도와 상품 기술서 사이의 비교순위에 의해 결정되며, 사용자와 에이전트 사이의 상품검색과 상품구매에 관한 정보는 지속적으로 사용자의 선호도 정보를 갱신하고 새로운 선호도 정보를 추론하는 데 사용된다. 이러한 방법에 의하여 사용자 선호도에 대한 적응성이 뛰어난 상품 추천 에이전트를 제공할 수 있으며, 전자상거래에서 구매자의 편의성을 증대시키는데 도움이 될 것으로 기대한다.

• Proceedings of the Korean Society for Cognitive Science Conference
• /
• 2005.05a
• /
• pp.145-150
• /
• 2005

최근 전자상거래에 대한 관심과 투자가 집중되면서 효과적인 사용자 인터페이스인 대화형 에이전트에 대한 연구가 활발히 진행되고 있다. 기존의 대화형 에이전트는 사용자의 질의에 미리 준비된 답변을 제공하기 때문에 복잡한 대화 상황을 처리하지 못한다. 이런 한계를 극복하기 위해 베이지안 네트워크 등의 기법을 이용한 사용자 의도 추론 기술이 연구되고 있다. 본 논문에서는 기존의 정보검색을 위한 대화형 에이전트에서 사용자 의도 추론의 성능을 높이기 위해 노드간의 의미 관계를 표현하는 정보를 결합한 시맨틱 베이지안 네트워크(Semantic Bayesian Network; SeBN) 모델을 제안한다. 단발적인 질의 분석이 아닌 점증적 질의 분석 방법을 바탕으로 불충분한 정보로 적절한 답변을 추론하지 못할 경우에MII(mixed-initiative interaction)를 수행하여 주어진 문제를 해결한다. 실제 모바일 검색 사이트에 제안하는 방법을 적용하여 유용성을 확인하였다.

• Journal of KIISE:Computing Practices and Letters
• /
• v.11 no.2
• /
• pp.180-191
• /
• 2005

The rapid growth of mobile communication technology has provided the expansion of mobile internet services, particularly mobile commerce takes much weight among them. Even though current mobile commerce service has serious problems which check its development, such as limited contents, expensive charge system and hardware restriction of mobile device, it is strongly expected as one of the next generation Internet services. In this paper, we summarize the problems like above and provide some total solution to meet them as follows: a function for automatic gathering of product information on online Internet and automatic translation it to data for mobile commerce, a middlelet application which provides functions for product search and order on the mobile device through off-line processing, and a function of user adaptive recommendation. We have actually designed and implemented the proposed system and verified the functions and effectiveness of the system.

• The KIPS Transactions:PartD
• /
• v.11D no.5
• /
• pp.1177-1188
• /
• 2004

Multi-agent systems have been developed for supporting intelligent collaboration of distributed and independent software entities and are be-ing widely used for various applications. For the collaboration among agents, conversation policies (or interaction protocols) mutually agreed by agents are used. In today's dynamic electronic market environment, there can be frequent changes in conversation policies induced by the changes in transaction methods in the market, and thus, the importance of ad hoc conversation policies is increasing. In existing agent platforms, they allow the use of only several standard or fixed conversation policies, which requires inevitable re implementation for ad hoc conversation policies and leads to inefficiency and intricacy. This paper designs an agent platform that supports ad hoc conversation policies and presents the prototype implementation. The suggested system includes an exchangeable and interpretable conversation policy model, a meta conversation procedure for exchanging new conversation policies, and a mechanism for performing actual transactions with exchanged conversation policies in run time in an adaptive way.