• 정보관리학회지
• /
• 제17권3호
• /
• pp.93-108
• /
• 2000

문헌정보학 교육은 실제적인 기술요소를 교육과정에 도입하여야 한다. 문헌정보학을 포함하여 전문직을 위한 어떤 종류의 교육이건 한 가지 필수적인 요소는 교육과정에서 실무를 준비시키는 것이다. 본 논문에서는 디지털 정보환경과 기술 도입, 그 기술 도입이 도서관환경에 미친 영향 그리고 미국의 변화된 교육과정을 고찰하였고 교유과정의 이상적인 버전을 제시하였다.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (B)
• /
• pp.7-9
• /
• 2004

With the development of e-commerce and information access, recommender systems have become a popular technique to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. In this paper, clustering technique is applied in the collaborative recommender framework to consider semantic contents available from the user profiles. We also suggest methods to construct user profiles from rating information and attributes of items to accommodate user preferences. Further, we show that the correct application of the semantic content information obtained from user profiles does enhance the effectiveness of collaborative recommendation.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (3)
• /
• pp.385-387
• /
• 2004

최근 지하철이나 버스 등의 교통수단을 이용하기 위해 비접촉식 카드를 이용한 IC카드 Reader가 많이 사용되고 있다. 이러한 IC카드 Header는 ID를 인증하기 위한 UserID를 Reader내부에 저장하고 있으며 UserID가 바뀔 때 마다 상위 시스템(서버)으로부터 전송받아 최신의 UserID를 가지고 있어야 한다. 교통시스템에서 사용되는 통신매체는 환경의 특수함으로 인해 낮은 전송속도를 이용하여 통신하고 있고, 그로인해 UserID를 전송할 때 시간이 많이 소모된다. UserID를 전송하는 동안에는 IC카드 Reader의 사용이 제한되기 때문에 UserID는 IC카드 Reader가 사용되지 않는 시간에 전송하고 있다. 많은 양의 UserID를 IC카드 Reader에 빠르게 전송하기 위해 UserID의 특성을 이용한 엔코딩(encoding) 기법을 적용 하여 UserID의 크기를 줄여 전송함으로써 전송시간을 줄이는 방법을 제안하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제14권2호
• /
• pp.122-129
• /
• 2014

Effective information gathering and retrieval of the most relevant web documents on the topic of interest is difficult due to the large amount of information that exists in various formats. Current information gathering and retrieval techniques are unable to exploit semantic knowledge within documents in the "big data" environment; therefore, they cannot provide precise answers to specific questions. Existing commercial big data analytic platforms are restricted to a single data type; moreover, different big data analytic platforms are effective at processing different data types. Therefore, the development of a common big data platform that is suitable for efficiently processing various data types is needed. Furthermore, users often possess more than one intelligent device. It is therefore important to find an efficient preference profile construction approach to record the user context and personalized applications. In this way, user needs can be tailored according to the user's dynamic interests by tracking all devices owned by the user.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.931-934
• /
• 2005

This paper describes an adaptive recommendation system that provides real-time personalized trading advice to the investors based on their profiles and trading information environment. A proposed system integrates Stochastic technical analysis and artificial neural network that incorporates an adaptive user modeling. The user model is constructed and updated based on initial user profile and recorded user interactions with the system. The information presented to each individual user is also tailor-made to fit the user's behavior and preference. A system prototype was implemented in JAVA. Experiments used to evaluate the system's performance were done on both human subjects and synthetic users. The results show our proposed system is able to rapidly learn to provide appropriate advice to different types of users.

• 한국컴퓨터정보학회논문지
• /
• 제21권7호
• /
• pp.9-16
• /
• 2016

Collaborative filtering(CF) uses the purchase or item rating history of other users, but does not need additional properties or attributes of users and items. Hence CF is known th be the most successful recommendation technology. But conventional CF approach has some significant weakness, such as the new user problem. In this paper, we propose a approach using word embedding with skip-gram for learning distributed item representations. In particular, we show that this approach can be used to capture precise item for solving the "new user problem." The proposed approach has been tested on the Movielens databases. We compare the performance of the user based CF, item based CF and our approach by observing the change of recommendation results according to the different number of item rating information. The experimental results shows the improvement in our approach in measuring the precision applied to new user problem situations.

• 한국콘텐츠학회:학술대회논문집
• /
• 한국콘텐츠학회 2008년도 춘계 종합학술대회 논문집
• /
• pp.614-621
• /
• 2008

사용자에게 제공될 수 있는 정보의 양이 많아졌을 뿐 아니라 정보의 유형도 매우 다양하며 정보를 사용하는 사용자의 환경과 유형이 매우 다양하기 때문에 사용자에게 적합한 최적의 정보를 필터링하는 것은 오늘날 매우 중요한 문제가 되었다. 이러한 필요성에 따라 본 연구는 다양한 단말기와 서비스 환경에 부합하는 콘텐츠 제공을 위한 사용자 적응형 콘텐츠 서비스를 위한 플랫폼을 설계한다. 정보 이용의 효율을 높이고자 사용자의 정보유형의 선호도 및 사용자의 정보사용 이력에 따라 정보를 필터링하고 사용자의 정보사용 환경을 고려하여 정보를 재구성하여 정보를 제공하는 사용자 적응형 콘텐츠 서비스를 제안한다. 선사박물관의 자료를 중심으로 사용자 콘텍스트에 따른 웹 서비스를 구현한다.

• 한국산업정보학회논문지
• /
• 제14권2호
• /
• pp.1-7
• /
• 2009

본 논문은 센서로부터 사용자의 환경정보를 수집하여 상황정보 프로파일을 생성히는 시스템을 제안한다. 본 논문에서는 유비쿼터스 컴퓨팅 환경에서의 상황인지에 대한 연구결과를 바탕으로 상황을 분류하고, 상황정보를 모델링하였다. 제안된 시스템은 다양한 일상생활에서 사용자에게 발생할 수 있는 주변환경 정보 및 신체정보를 수집하여, 상황정보 프로파일을 생성함으로써 콘텐츠 적응화 서비스를 지원할 수 있다.

• Asia pacific journal of information systems
• /
• 제14권1호
• /
• pp.101-123
• /
• 2004

User satisfaction has been widely used by information system(IS) researchers as the most appropriate surrogate variable for the systems success since Bailey and Pearson(1983) provided their user satisfaction measurement. Because user satisfaction is a perceived performance measure by users, not a real or objective measure for systems success, however, perceived user satisfaction by users may not be exactly identical with the real systems performance. In this regard, if the user's ultimately perceived satisfaction is different from the real systems performance, we need to investigate why these two measures are different and which factors may cause the difference. From the perspective of disconfirmation of user expecations, this study examined why user satisfaction and real systems performance may not be identical each other. Expectaion-disconfirmation theory which has had a central role in marketing in explaining the effects of expectation and disconfirmation on consumer satisfaction was similarly adopted in this study to explain the role of expectation and disconfirmation in user satisfaction in the IS environment. Based on the expectation-disconfirmation theory, the current study developed a research model to examine the effects of expectation, system performance, and disconfirmation on user satisfaction in particular. Six research hypotheses derived from the research model were empirically tested using the partial least squares(PLS) method. The results of the statistical analysis indicate that the effects of system performance and disconfirmation were fairly strong on user satisfaction, while the user's expectation has shown insignificant influences on user satisfaction.

• Journal of Information Science Theory and Practice
• /
• 제2권3호
• /
• pp.6-17
• /
• 2014

The purpose of this study is to examine to what extent the context in which people interact with online information affects people's credibility perceptions. In this study, credibility assessment is defined as perceptions of credibility relying on individuals' expertise and knowledge. Context has been characterized with respect to three aspects: Context as user goals and intentions, context as topicality of information, and context as information activities. The data were collected from two empirical studies. Study 1 was a diary study in which 333 residents in Michigan, U.S.A. submitted 2,471 diary entries to report their trust perceptions associated with ten different user goals and nine different intentions. Study 2 was a lab-based study in which 64 subjects participated in performing four search tasks in two different information activity conditions - information search or content creation. There are three major findings of this study: (1) Score-based trust perceptions provided limited views of people's credibility perceptions because respondents tended to score trust ratings consistently high across various user goals and intentions; (2) The topicality of information mattered more when study subjects assessed the credibility of user generated content (UGC) than with traditional media content (TMC); (3) Subjects of this study exerted more effort into making credibility judgments when they engaged in searching activities than in content creation. These findings indicate that credibility assessment can or should be seen as a process-oriented notion incorporating various information use contexts beyond simple rating-based evaluation. The theoretical contributions for information scientists and practical implications for web designers are also discussed.