• Journal of the Korean Society for information Management
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• v.33 no.1
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• pp.317-336
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• 2016

Nowadays users spend more time and effort to find what they want because of information overload. To solve the problem, scientific article recommendation system analyse users' needs and recommend them proper articles. However, most of the scientific article recommendation systems neglected the core part, user profile. Therefore, in this paper, instead of mean which applied in user profile in previous studies, New TPIPF (Topic Proportion-Inverse Paper Frequency) was applied to scientific article recommendation system. Moreover, the accuracy of two scientific article recommendation systems with above different methods was compared with experiments of public dataset from online reference manager, CiteULike. As a result, the proposed scientific article recommendation system with TPIPF was proven to be better.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.434-441
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• 2016

Using bigdata analysis procedures, the present study sought to review and explore the various aspects of self-disclosure and boundary impermeability of worldwide twitter users. A total of 415 million tweets issued by 54 million users were collected during 6 months and the users of top 10 languages were investigated. And the effect of languages of twitter users on the boundary impermeability, disclosure rate of user profile, profile image, geographical information, URL in profile and user description were analyzed in this study. The results showed that the boundary impermeability and all the self-disclosure rates of twitter users (profile, profile image, geographical information, URL in profile, user description) were significantly (p<0.001) different among language groups of users. The self-disclosure rates and the average points of Portuguese, Indonesian and Spanish users were higher than those of Arabic, Japanese, Turkish and Korean users. The results also showed a positive relationship between boundary impermeability and the number of tweets (including retweets) issued by each users.

• Journal of Information Management
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• v.8 no.5
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• pp.130-140
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• 1975

이용자(利用者) 중심(中心)의 대화방식(對話方式) 시스팀을 개발(開發)하고 시험(試驗)하였다. 2년(年)동안 280개의 프로파일로 CA - Condensates 데이터 베이스내에서 정보(情報)를 검색(檢索)해 보았다. 그 시스팀의 작업능률(作業能率)을 사용(使用)한 데이터 베이스와 하드웨어의 구조(構造), 소프트웨어 패키지, 이용자(利用者)의 수(數), 그리고 정보(情報)센터에서 제공(提供)한 보조(補助)에 따라 평가(評價)하였다. 대화식(對話式) 검색방법(檢索方法)이나 이용자(利用者)의 요구(要求)를 양화(量化)하는 것, 그리고 여러가지 분야별(分野別)로 검색(檢索)하는 방법(方法) 등 이용자(利用者)의 요구(要求)를 보다 충실(充實)하게 만족(滿足)시킬 수 있는 여러가지 방법(方法)들을 논의(論議)하였다. 모든 정보(情報)시스팀의 목적(目的)은 적시(適時)에 올바른 정(情)보를 적자(適者)에게 제공(提供)하는 것이라고 잘 알려져 있다. 다시 말해서, 정보(情報)시스팀의 주요목적(主要目的)은 이용자(利用者)의 요구(要求)를 충족(充足)시켜 주는 것이다. 이러한 관념(觀念)의 변화(變化)는 정보처리(情報處理)에 큰 변화(變化)를 가져와 정보(情報)시스팀의 적응성(適應性)을 증가(增加)시키기 위해 여러 가지 새로운 방법(方法)들이 개발(開發)되었다. 정보(情報)시스팀들 사이의 상호작용(相互作用), 사람과 컴퓨터와의 대화(對話), 그리고 컴퓨터의 조력(助力)으로 이용자(利用者)의 프로파일을 작성(作成)하는 것 등은 이용자(利用者)의 요구(要求)를 존중(尊重)하고, 필요(必要)한 정보(情報)를 쉽게 찾기 위해서 고안(考案)된 것이다. 한편, 우리들은 이용자(利用者)의 특성(特性)이나 배경(背景), 그리고 문헌(文獻)에 대한 그의 습성(習性) 등에 대해서 얼마나 모르고 있는가를 깨닫게 된다. 상기(上記)의 내용(內容)을 요약(要略)하면, 근대정보(近代情報) 시스팀은 다음의 필요조건(必要條件)을 만족(滿足)해야 한다. 1) 이용자(利用者)의 요구(要求)에 호응(呼應)하기 위해서 적합(適合)한 일련(一連)의 정보(情報)를 제공(提供)해야 한다. 2) 이용자(利用者)와의 관계(關系)에서 시스팀은 적극적(積極的)이어야 한다. 즉, 프로파일 검색공식(檢索公式)에서 유발(誘發)되는 잘못을 지시(指示)하고 지적(指適)할 수 있어 야 한다. 나아가서 컴퓨터의 조력(助力)으로 프로파일을 작성(作成)하고 쉽게 수정(修正)할 수 있는 바람직하다. 우리들은 상기(上記)한 필수조건(必須條件)에 일치(一致)하도록 노력(努力) 하고 Bratislava에 위치(位置)하고 있는 슬로박 과학원(科學院)의 무기화학연구소(無機化學硏究所)와 화학공업경제연구소(化學工業經濟硏究所)가 공동(共同)으로 개발(開發)한 시스팀이 상기(上記)의 특수성(特殊性) 최소(最少)한 몇가지 도입(導入)하였다. 시스팀은 CACS라는 작업명하(作業名下)에서 운영(運營)되었다. 대략 15개월동안 280여개의 프로파일로 CA- Condensates 데이터베이스에서 정보(情報)를 검색(檢索)하여 이용자(利用者)들에게 최신정보(最新情報) 주지사업(周知事業)을 해 보았다. 우리들은 시스팀의 작업능률(作業能率)을 평가(評價)하고 이용자(利用者)의 요구(要求)를 만족(滿足)시키는 최선(最善)의 방법(方法)을 모색(摸索)하였다. 우선 이용자(利用者)와 시스팀사이를 밀접(密接)하게 연결(連結)하는데 중점(重點)을 두었다. 작업능률(作業能率Z)을 분석(分折)해 보고 우리들은 효율(效率)에 영향(影響)을 주는 인자(因子)는 다음의 4가지 주요분류(主要分類)에 속한다는 결론(結論)을 얻었다. (1) 검색(檢索)하는 데이터 베이스 (2) 情報시스팀, 소프트웨어 패키지 그리고 하드웨어 구조(構造) (3) 이용자(利用者)의 특성(特性)과 그의 요구(要求) (4) 정보(情報)센터가 이용자(利用者)에게 제공(提供)하는 보조(補助)

• Journal of the Korean Society for Library and Information Science
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• v.39 no.3
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• pp.75-91
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• 2005

The popularization of the internet has produced an explosion in amount of the information. The importance of web personalization is being more and more increased. The personalization is realized by learning user's interest. User's interest is changing continuously and rapidly. We use user's profile to represent user's interest. User's profile is updated to reflect the change of user's interest. In this paper we present an adaptive learning algorithm that can be used to reflect user's interest that is changing with time. We propose the User's profile model. With this profile user's interest is learned based on user's feedback. This approach has applied to develop hybrid recommendation system.

• Journal of Information Management
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• v.8 no.2
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• pp.62-65
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• 1975

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.61-82
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• 2004

The purpose of this study is to examine how the commonly known profile of public library users was described, by reviewing the literature published in the United States before the 1990s, when information environment of the public has been drastically changed. The profile of users as the socio-economically advantaged, active participants, and communication elites, has little changed since Berelson's study in the 1940s. Continuing research on users, however, are still needed to better understand their needs and behavior, facing the change since the 1990s.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.194-210
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• 2022

The user-centered EV charging infrastructure construction policy the government is aiming for can increase convenience for electric vehicle users and bring new electric vehicle users into the market. This study was conducted to provide an in-depth understanding of the charging behaviors of actual electric vehicle users, which can be used as basic information for the electric vehicle charging infrastructure. Based on charging diary data collected for a week, the charging of electric vehicles was analyzed on a daily and weekly basis, and sequence analysis and latent class analysis were used. As a result, five daily charging profiles and four weekly charging profiles were identified, which are expected to contribute to revitalizing the electric vehicle market by providing key information for decision-making by potential electric vehicle users as well for establishing user-centered charging infrastructure policies in the future.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.2
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• pp.259-276
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• 1998

This study is to contribute to develop adaptive information systems meeting inside information needs as well as represented information needs, and dealing with every levels of users and user's preferences. Also, this study is to present a method of developing adaptive information system through developing user profile using machine teaming and decision tree, applying relevance feedback using merged vector, and applying user feedback.

• Journal of the Korean Society for information Management
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• v.20 no.4 s.50
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• pp.113-134
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• 2003

With SDI service provided in libraries and information centers traditionally, this paper studies component technologies and structure of system platform in PIS(personalization information service based on the customized information service served currently in some institutions. The PIS system should provide relevant information as an output through the learning system analyzing user information searching behavior as an input value with personal profile information. To do it, this paper studies requirements and algorithms to develop PIS, and proposes learning system and recommendation system as core components in PIS.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.4
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• pp.77-102
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• 2011

The purpose of this study is to design, implement and evaluate a personalized search system using gathered information on users to provide more accurate search results. For this purpose, a hybrid-based user profile is constructed by using subject classification. In order to evaluate the performance of the proposed system, experts directly measured and evaluated MRR, MAP and usability by using the Korean journal articles of science and technology DB. Its performance was better than the general search system in the area of "Computer Science" and "Library and Information Science". Especially better results were shown when tested on ambiguous keywords. Evaluation through in-depth interviews proved that the proposed personalized search system was more efficient in looking up and obtaining information. In addition, the proposed personalized search system provided a variety of recommendation systems which proved helpful in navigating for new information. High user satisfaction ratings on the proposed personalized search system were another proof of its usefulness. In this study, we were able to prove through expert evaluation that the proposed personalized search system was more efficient in information retrieval.