• 산업공학
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• 제19권3호
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• pp.225-235
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• 2006

In this paper, we propose an intelligent e-commerce meta-search engine which integrates distributed e-commerce sites and provides a unified search to the sites. The meta-search engine performs the following functions: (1) the user is able to create a category-based user query, (2) by using the WordNet, the query is semantically refined for increasing search accuracy, and (3) the meta-search engine recommends an e-commerce site which has the closest product information to the user’s search intention by matching the user query with the product catalogs in the e-commerce sites linked to the meta-search engine. An experiment shows that the performance of our model is better than that of general keyword-based search.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2005년도 공동추계학술대회
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• pp.346-355
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• 2005

In this paper, we propose a meta-search engine which provides distributed product information through a unified access to multiple e-commerce. The meta-search engine proposed in this paper performs the following functions: (I) The user is able to create a category-based user query, (2) by using the WordNet, the query is semantical refined fined for increasing search accuracy, and (3) the meta-search engine recommends an e-commerce site which has the closest product information to the user's search intention, by matching the user query with the product catalogs in the e-commerce sites linked to the meta-search engine. An experiment shows that the performance of our model is better than that of general keyword-based search.

• 대한가정학회지
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• 제41권8호
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• pp.19-31
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• 2003

This study was intended to present the plan for preventing and solving the seriousness of the consumer problem perceived in the e-commerce. For this purpose, 723 questionnaires were distributed to university As a result of analysis, the following findings were obtained: 1) It was found that e-commerce users had higher knowledge of the degree of internet un, the ability to use information on the internet, the disposition of computerization, and e-commerce related consumer than e-commerce non-users. 2) It was found that e-commerce non-users had the higher level of perceived seriousness of the consumer problem than e-commerce users. Especially, it was found that e-commerce non-users had the high level of perceived seriousness of the consumer problem related to the problem of exchange, termination and after-sale nice and the leakage of exchange, termination and after-sale service and the leakage of private information e-commerce user. 3) It was found that university consumers' perceived seriousness of the consumer problem in e-commerce over the internet showed a significant difference in the ability to use information on the internet between e-commerce users and non-users.

• 디지털산업정보학회논문지
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• 제18권4호
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• pp.85-96
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• 2022

Personalized recommendation technology is one of the most important technologies in electronic commerce environment. It helps users overcome information overload by suggesting information that match user's interests. In e-commerce environment, both mobile device users and smart device users have risen dramatically. It creates new challenges. Our method suggests product information that match user's device interests beyond only user's interests. We propose a device-centered personalized recommendation method. Our method uses both purchase and share behavior for user's devices interests. Moreover, it considers data type preference for each device. This paper presents a new recommendation method and algorithm. Then, an e-commerce scenario with a computer, a smartphone and an AI-speaker are described. The scenario shows our work is better than previous researches.

• 지식경영연구
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• 제20권4호
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• pp.169-183
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• 2019

The growth of mobile commerce (m-commerce) has been accelerated around the world. Why do e-retailers have to put a great deal of effort for the distribution of their mobile apps? The literature has paid little attention to the influence of the introduction of an e-commerce app on shopping behaviors of consumers. By analyzing the dataset of 2,342 users in Korea, this study aims to broaden our understanding of mobile shopping app usage across competing e-retailers and different channels. We found that a user's prior usage of a specific e-commerce mobile app increases her subsequent usage of its website through a mobile web browser. Thus, mobile apps do not cannibalize the mobile web channel, and there could be a complementary relationship. We also found that a user's usage of competitors' apps is positively associated with her subsequent usage of a specific e-commerce app. Because many consumers search products and compare prices across multiple e-retailers, having a mobile app helps an e-retailer be exposed to more potential consumers. This study is among the first to study the role of mobile apps in e-commerce by showing the dynamics of cross-channel and cross-vendor usage by a user.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.476-479
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• 2005

The information available on the Internet has become widely used, primarily due to the ability of Web based E-Commerce and M-Commerce Retrieval Engines to find useful information for users. However, present day Commerce Retrieval Engines are far from perfect because they return results based on simple user keyword matches without any regard for the concepts in which the user is interested. In this thesis, we design and evaluate a Recommender system for web context aware based information retrieval using user profiles. Also, we designed personalization framework in ubiquitous environment based both e-commerce and m-commerce and presented the interaction of user profile including User XQuery pattern in semantic web.

• Asia pacific journal of information systems
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• 제16권3호
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• pp.159-176
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• 2006

Collaborative filtering is one of the popular techniques for personalized recommendation in e-commerce. In collaborative filtering, user profiles are usually managed per product category in order to reduce data sparsity. Product diversification of Internet storefronts and multiple product category sales of e-commerce portals require cross-product category usage of user profiles in order to overcome the cold start problem of collaborative filtering. In this paper, we study the feasibility of cross-product category usage of user profiles, and suggest a method to improve recommendation performance of cross-product category user profiling. First, we investigate whether user profiles on a product category can be used to recommend products in other product categories. Furthermore, a way of utilizing user profiles selectively is suggested to increase recommendation performance of cross-product category user profiling. The feasibility of cross-product category user profiling and the usefulness of the proposed method are tested with real click stream data of an Internet storefront which sells multiple product categories including books, music CDs, and DVDs. The experiment results show that user profiles on a product category can be used to recommend products in other product categories. Also, the selective usage of user profiles based on correlations between subcategories of two product categories provides better performance than the whole usage of user profiles.

• 방송공학회논문지
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• 제10권4호통권29호
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• pp.610-620
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• 2005

본 연구는 프로그램 연동형 T-Commerce 이용 의도에 영향을 미치는 소비자 수용 요인을 파악하기 위하여 지상파 양방향 디지털 방송에 노출된 시청자들을 대상으로 이들이 e-Commerce에 대해 지각하는 유용성 및 이용 용이성이 T-Commerce 이용 의도에 미치는 영향을 실증 분석하였다. 이 과정에서 사용자가 보유한 새로운 기술에 대한 혁신성이 유용성이나 이용 용이성과 이용 의도간의 관계를 조절하는 지에 대한 분석이 병행되었다. 분석 결과 양방향 매체를 대상으로 실시된 선행 연구들과 마찬가지로 지각된 유용성은 이용 의도에 유의한 영향을 미치는 반면 지각된 이용 용이성은 유의한 영향을 미치지 못하는 것으로 나타났다. 또한, 다른 양방향 매체들을 대상으로 실시된 기존의 연구 결과와는 달리 이용자의 혁신성이 지각된 유용성이 이용 의도에 미치는 영향을 조절하는 것으로 나타났다. 이러한 연구 결과를 통하여 T-Commerce의 시행 단계에 따라 시청자 유인 전략이 달라져야 한다는 시사점을 얻을 수 있었다.

• 경영과정보연구
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• 제25권
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• pp.371-386
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• 2008

In this study, the hypothesized model of internet user satisfaction in e-commerce environment is developed and the relationships among constructs in the model are examined. A Confirmatory factor analysis is employed to analyze the relationships between the multiple dependent variables and independent variables.

• 정보처리학회논문지D
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• 제11D권5호
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• pp.1205-1212
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• 2004

전자상거래 시스템의 보급이 활성화되기 시작하면서, 사용자의 필요와 욕구에 밀착한 적응형 전자상거래 에이전트의 필요성이 증대되고 있다. 이와 같은 적응형 전자상거래 에이전트는 사용자의 행위를 모니터하고 자동 분류하여 사용자의 취향을 학습하는 기능을 요하게 되었다. 이러한 기능을 가지는 적응형 전자상거래 에이전트를 구축하기 위해서, 본 논문에서는 사용자 개인의 관심정보와 선호하는 상품에 대한 호감도를 고려한 적응형 전자 상거래 에이전트 시스템을 제안한다. 제안하는 시스템은 사용자의 구매 행위에 적응력을 가질 수 있도록 보다 정확한 사용자 프로파일을 구축하고, 이와 같은 사용자 프로파일을 기반으로 사용자에게 불필요한 검색과정 없이 필요한 상품 정보를 제공 할 수 있도록 한다. 본 시스템에서는 모니터링을 통하여 사용자 의도를 파악하는 모니터 에이전트, 사용자의 행동성향을 학습 한 후 행동 패턴이 유사한 그룹을 참조하는 유사도 참조 에이전트, 사용자의 행위의 변화에 따른 개인화된 행동 DB를 구축할 수 있는 관심 추출 에이전트로 구성하였다.