• Journal of muscle and joint health
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• v.28 no.3
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• pp.217-222
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• 2021

Background: The reaction of nurses to the advent of artificial intelligence (AI) during the fourth industrial revolution era remains questionable. Understanding Florence Nightingale's achievements may provide valuable lessons that will be helpful to contemporary nurses. Aims: To understand Nightingale's nursing philosophy and methods and provide suggestions for future nursing practice, education, research, and health policy. Source of evidence: Literature. Discussion/Conclusion: Just as Nightingale captured the situation of her time and introduced latest scientific methods, modern nurses need to learn from Nightingale's drastic actions to meet social needs. Nursing can regain a solid humanistic foundation by returning to core values of nursing and humanities, while simultaneously adopting state-of-the-art technologies. Implications for Nursing Policy: AI-driven technologies will advance nursing services and provide greater human-centered and personalized care by eliminating iterative and labor-intensive tasks. Nursing educational policy should support the advancement of nursing curricula to develop AI competencies and specialists within the nursing field.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.729-732
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• 2007

맞춤형 방송 솔루션은 디지털 TV 서비스 외에도, 향후 유망기술로 주목 받고 있는 IPTV, DMB 등의 다양한 방송 및 멀티미디어 서비스에 적용이 가능하다. 본 연구에서는 맞춤형 방송 서비스의 객관적인 평가를 위한 성능평가 방법을 제안한다. 정보검색 시스템 평가에 사용하는 정확률, 재현률과 역순위 평균 수치를 적용하여 맞춤형방송의 추천결과와 실제 시청자의 시청 프로그램의 차이를 분석하여 맞춤형 방송 시스템의 정확도와 사용자 만족도를 통계적으로 평가 가능한 메카니즘을 제안한다. 그 동안 평가가 이루어지지 않았던 맞춤형 방송 서비스를 복합적으로 평가하는 방법론을 제안함으로써, 맞춤형 방송 시스템의 지속적인 성능향상과 연구개발에 기여할 것이다. 또한, 맞춤형 방송 서비스의 산업화와 다양한 장비로의 확산에도 기여할 것으로 기대된다.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of the Korean Society of Costume
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• v.67 no.3
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• pp.115-132
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• 2017

This study recognizes the importance of the social network platform as a new fashion media, and analyzes the significance of various digital fashion images, based on the 'Aura' theory of Walter Benjamin. The concept of "Disappearance of Artistic Aura" can be summarized into three discussions: 1) the change in the way of artistic perception, which is changes in value from worship to exhibition. 2) the change in the way of artistic acceptance, from personal to mass. 3) the emergence of new artistic concepts such as camera and film. By reviewing characteristics of the $21^{st}$ digital replication era, the study tried to discover and evaluate the expanded significance of the 'Aura' represented on digital fashion images, which are infinitely generated, modified, reproduced, transmitted, and shared in social network environments. The 'Burberry Instagram' was chosen as the subject of the study. The study reviewed around 2,500 images, which were uploaded from February 2011 to July 2016, and selected 200 images deemed the most representative of Burberry, and categorized and analyzed by the extended concept of 'Aura'. The study results as follows: First, the 'Aura' in digital fashion image appearing on social network platforms signifies the expansion of product value in fashion, and it also represents inherited traditions and modernization of images. Second, it also signifies the democratization and globalization of fashion through the open replication and sharing as well as the interaction of criticism and acceptance. Third, it signifies the personalized taste and fashion as everyday lifestyle, through personalized services, securing playful space, and real-time updates.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.945-954
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• 2002

Clickstream is the information which demonstrate users' path through web sites. Analysis of clickstream shows how web sites are navigated and used by users. Clickstream of online web sites contains effective information of web marketing and to offers usefully personalized services to users, and helps us understand how users find web sites, what products they see, and what products they purchase. In this paper, we present an extended web log system that add to module of collection of clickstream to understand users' behavior patterns In web sites. This system offers the users clickstream information to database which can then analyze it with ease. Using ADO technology in store of database constructs extended web log server system. The process of making clickstreaming into database can facilitate analysis of various user patterns and generates aggregate profiles to offer personalized web service. In particular, our results indicate that by using the users' clickstream. We can achieve effective personalization of web sites.

• Journal of Society of Preventive Korean Medicine
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• v.17 no.2
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• pp.69-78
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• 2013

Objectives : Health cooperative movement is of increasing concern among medical consumers and professionals in Korea. Most health cooperative clinics provide Western Medicine and Korean Medicine(KM) to patients. This study aimed to evaluate the primary care level of health cooperative KM clinics and compare it with local KM clinics in Korea. Methods : Face to face survey was performed at the 3 health cooperative KM clinics and 5 local KM clinics with the Korean Primary Care Assessment Tool (KPCAT). The KPCAT consists of 5 domains (21 items): first contact (5), coordination function (3), comprehensiveness (4), family/community orientation (4), and personalized care (5). Subjects were patients or guardians who had visited KM clinics five times or more during the last 3 months. We compared primary care scores of each domain between health cooperative KM clinics and local KM clinics. Results : Data were collected from 200 respondents (100 patients from health cooperative KM clinics and 100 local KM clinics). Total average scores of the KPCAT for health cooperative clinics and local KM clinics were $81.1{\pm}12.0$ and $75.4{\pm}9.5$, respectively. Among primary care domains, personalized care was the highest ($89.2{\pm}12.0$, $89.6{\pm}8.4$, respectively), and comprehensiveness function was the lowest ($68.5{\pm}22.5$, $54.5{\pm}22.0$, respectively). Significant differences between two groups were noted in comprehensiveness function (68.5 vs. 54.5, P=0.000), family-community orientation (79.5 vs. 73.0, P=0.004), first contact(89.2 vs 84.0, p=0.001) and coordination function(74.0 vs 68.7, p=0.025). Conclusions : Based on the patients assessment, health cooperative KM clinics provide more primary care-oriented services than local KM clinics. This means that health cooperative clinic can be one of alternatives to strengthen the primary health care in Korea. Future researches are recommended to measure patients satisfaction and treatment effectiveness in the health cooperative clinics.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.81-99
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• 2017

Technical documents are important research outputs generated by knowledge and information society. In order to properly use the technical documents properly, it is necessary to utilize advanced information processing techniques, such as summarization and information extraction. In this paper, to extract core information, we automatically extracted the terminologies and their definition based on definitional sentences patterns and the structure of technical documents. Based on this, we proposed the system to build a specialized terminology dictionary. And further we suggested the personalized services so that users can utilize the terminology dictionary in various ways as an knowledge memory. The results of this study will allow users to find up-to-date information faster and easier. In addition, providing a personalized terminology dictionary to users can maximize the value, usability, and retrieval efficiency of the dictionary.

• Journal of the Korean Society for information Management
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• v.23 no.3 s.61
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• pp.91-125
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• 2006

Recent advancements in information technology and the Internet have caused an explosive increase in the information available and the means to distribute it. However, such information overflow has made the efficient and accurate search of information a difficulty for most users. To solve this problem, an information retrieval and filtering system was developed as an important tool for users. Libraries and information centers have been in the forefront to provide customized services to satisfy the user's information needs under the changing information environment of today. The aim of this study is to propose an efficient information service for libraries and information centers to provide a personalized recommendation system to the user. The proposed method overcomes the weaknesses of existing systems, by providing a personalized hybrid recommendation method for multimedia contents that works in a large-scaled data and user environment. The system based on the proposed hybrid method uses an effective framework to combine Association Rule with Collaborative Filtering Method.

• Journal of Information Technology Application
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• v.3 no.1
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• pp.1-21
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• 2001

The explosive growth of the Internet and the increasing popularity of the World Wide Web have generated significant interest in the development of electronic commerce in a global online marketplace. The rapid adoption of the Internet as a commercial medium is rapidly expanding the necessity of Web advertisement as a new communication channel. if proper Web advertisement could be suggested to the right user, then effectiveness of Web advertisement will be raised and it will help company to earn more profit. So, this article describes a personalized advertisement technique as a part of intelligent customer services for an electronic newspaper provide. Based on customers history of navigation on the electronic newspapers pages, which are divided into several sections such as politics, economics, sports, culture, and so on, appropriate advertisements (especially, banner ads) are chosen and displayed with the aid of machine learning techniques, when customers visit to the site. To verify feasibility of the technique, an application will be made to one of the most popular e-newspaper publishing company in Korea.

• Journal of the Korea Society of Computer and Information
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• v.16 no.9
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• pp.19-26
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• 2011

Users want to receive customized service using users' personal device. To fulfill this requirement, the mobile device has to support a lot of functions. However, the mobile device has limitations such as tiny display screens. To solve this limitation problem and provide customized service to users, this paper proposes the environment to provide services by sharing resources and the method to recommend user-suitable resources among sharable resources. For the resource recommendation, This paper analyzes user's behavior pattern from usage history and proposes the method for recommending customized resources. This paper also shows that the approach is reasonable one for resource recommendation through the satisfaction evaluation.