• Directory of Electronic and Electrical Manufacturers
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• s.1995-96
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• pp.3-143
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• 1995

• Directory of Electronic and Electrical Manufacturers
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• s.2001-02
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• pp.3-130
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• 2001

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.153-169
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• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• Proceedings of the Korea Contents Association Conference
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• 2003.11a
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• pp.60-64
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• 2003

Individualization serverces to be persuited in most web sites are not one automated by system but collectivization services provided into several groups with information collected in initial register. Also, as most of the web sites provide individualization services according to environmental setting fitted by each individual, it is hard to offer to provide them with analyzing members by system itself. In this paper, as we store behavior characters of members on web surfing into member database and anlyze them automatically, system itself enables to provide individualization services.

• 정보화사회
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• s.103
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• pp.62-63
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• 1996

제일씨앤씨라는 회사에 대해 최근 신문 등의 매체에 자주 오르내리는 까닭에 SI업계에 종사하는 분들은 한 번쯤 들어보았을 것이다. 사실이 회사는 설립된 지 1년밖에 안된 신생 SI기업이지만 제일제당그룹과 관련이 있다든지, SI업계의 새로운 다크호스라든지, 유통VAN사업에 진출했다든지 하는 내용으로 최근 지면상에 자주 오르내리고 있어, 협회 회원사 여러분들에게 제일씨앤씨에 대한 자세한 소개를 하고자 한다.

• Digital Contents
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• no.3 s.58
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• pp.53-55
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• 1998

경쟁정보전문가협회(SCIP : Society of Competitive Intelligence Professionals)는 1986년에 설립된 단체로 전세계의 회사와 컨설팅업체의 다양한 회원으로 구성되어 있다. 이 협회는 CI분야의 급격한 성장에 따라 비즈니스 전문가를 위한 교육을 준비하고 네트워킹 기회를 부여하는 세계적인 비영리 단체이다. 현재 회원수는 약 6천명 이상으로 매년 40%의 비율로 증가하고 있다.

• 정보화사회
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• s.21
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• pp.44-45
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• 1989

• 정보화사회
• /
• s.2
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• pp.62-63
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• 1988

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.43-46
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• 1997

한국감성과학회의 홈페이지의 구성을 위하여 형식 문법(HTML ;Hyper Text Markup Language)의 작성은 넷스케이프(NETSCAPE)의 컴포저(composer)을 이용하였으며, 필요한 그림 및 아이콘(Icon)은 Adobe photoshop 4.0버전으로 작성하였고, Map This 1.3버전을 이용하여 이미지 맵들을 구성하여 학회의 홈페이지를 만들었다. 감성과학회의 홈페이지를 시작으로 회원마당/가입안내, 학회안내, 행사일정 및 소식, 학회논문 검색, 국제정보를 하부구조로 구성하였으며, 각 하부구조 밑에 또 다른 하부구조를 구성하도록 하였다. 이렇게 본 학회의 홈페이지를 구축함으로써 쉽게 학회의 행사 및 소식을 회원에게 전달할 수 있으며, 학회의 가입 및 신청과 논문 투고요령, 학회에 관련한 국제정보 및 학회의 조직 및 학회 강령을 각 회원 및 비회원에게도 편리하게 홍보할 수 있으며, 세계적인 수준의 학회로도 발전해 갈 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.124-127
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• 2020

이 연구에서 개발한 헬스장 회원-트레이너 매칭 앱은 보디빌딩 헬스 회원과 트레이너를 매칭하여 관리할 수 있다. 즉, 보디빌딩 헬스장에 등록한 회원은 이 어플을 이용하여 명시적으로 원하는 조건이나 자연적으로 자신에게 알맞은 트레이너를 선택하거나 추천받을 수 있다. 트레이너의 추천은 유사도 측정 알고리즘을 통하여 이루어진다.