• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.310-315
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• 2001

We are focusing on an approach which handle a general Web as a resource in order to support self-directed learning for a student. Then, we are developing a Web based learning environment "Web-Retracer"for utilizing Web as teaching materials by a user′s Annotation. Although the learner can share the Web resource that the others utilized in this environment, Web resources unsuitable for a student′s needs becomes hindrance about her/his self-directed learning. In this paper, we propose a recommending method of the resource united with a student′s needs on the basis of a student′s learning and Web browsing history. This method analyzed the feature peculiar to a resource, and extracts the resource with which the needs of the feature and a student agreed.

• 한국컴퓨터정보학회논문지
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• 제22권3호
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• pp.35-43
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• 2017

In IoT(Internet of Things) environment, users want to receive customized service by users' personal device such as smart watch and pendant. To fulfill this requirement, the mobile device should support a lot of functions. However, the miniaturization of mobile devices is another requirement and has limitation such as tiny display. limited I/O, and less powerful processors. To solve this limitation problem and provide customized service to users, this paper proposes a collaboration system for sharing various computing resources. The paper also proposes the method for reasoning and recommending suitable resources to compose the user-requested service in small device with limited power on expected time. For this goal, our system adopts MBTI(Myers-Briggs Type Indicator) to analyzes user's behavior pattern and recommends personalized resources based on the result of the analyzation. The evaluation in this paper shows that our approach not only reduces recommendation time but also increases user satisfaction with the result of recommendation.

• 한국컴퓨터정보학회논문지
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• 제16권9호
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• pp.19-26
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• 2011

최근 스마트 폰과 같은 다양한 모바일 장치들의 개발과 함께 사용자는 자신의 모바일 단말을 이용하여 개인화된 서비스를 제공받기를 원한다. 이러한 요구사항을 만족하기 위하여 모바일 장치들은 많은 기능을 제공해야하지만 모바일 장치가 소형화됨에 따라 작은 디스플레이 장치, 제한적인 입력 장치 그리고 부족한 파워와 같은 자원 제약성을 갖는다. 본논문은이러한자원의제약성을해결하고사용자에게개인화된서비스를제공하기위하여유비쿼터스환경에서 컴퓨팅 자원을 공유하여 사용자에게 서비스를 제공하기 위한 환경을 제안한다. 또한 다양한 자원들 가운데 사용자의 상황과 개인 선호도를 기반으로 최적의 자원을 추천하기 위한 방법을 제안한다. 이러한 자원 추천을 위하여 본 논문에서는 사용자의 사용 이력으로부터 행동 유형을 분석하고 이를 기반으로 개인화된 자원을 추천하기위한 방법을 사용한다. 또한 논문은 제안한 방법을 구현하고 만족도를 평가하여 유효성을 보인다.

• Asian Pacific Journal of Cancer Prevention
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• 제14권1호
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• pp.153-158
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• 2013

This paper reports on part of a large study to identify competencies of oncology nurses in Malaysia. It focuses on oncology nurses' communications-related competency. As an important cancer care team member, oncology nurses need to communicate effectively with cancer patients. Literature shows that poor communication can make patients feel anxious, uncertain and generally not satisfied with their nurses' care. This paper deliberates on the importance of effective communication by oncology nurses in the context of a public hospital. Four focus group discussions were used in this study with 17 oncology/cancer care nurses from Malaysian public hospitals. The main inclusion criterion was that the nurses had to have undergone a post-basic course in oncology, or have work experience as a cancer care nurse. The findings indicated that nurses do communicate with their patients, patients' families and doctors to provide information about the disease, cancer treatment, disease recurrence and side effects. Nurses should have good communication skills in order to build relationships as well as to provide quality services to their patients. The paper concludes by recommending how oncology nursing competencies can be improved.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.596-600
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• 2009

Web 2.0의 사용자 참여, 개방, 공유 중심의 인터넷 환경은 대량의 다양한 정보가 생성, 공유되고 있으며, 효율적인 검색기법만으로는 원하는 시점에 필요한 정보를 효과적으로 제공받지 못하는 상태이므로, 정보검색이나 필터링 과정에 추가적인 기법들이 요구되고 있다. 또한, 유비쿼터스 환경이 구축됨에 따라 정보검색은 장소와 시간에 관계없이 수행되며, 상황과 환경에 능동적이며 실시간적인 응답을 요구받고 있으므로. 정보검색이나 추천과정에서는 사용자의 상황과 요구조건에 적합한 정보를 결정하는 효율적인 리소스 매칭기법이 필수적이다. 본 논문에서는 연구개발을 주 업무로 하는 임의조직을 대상으로 구성원들의 정보활동을 효과적으로 지원하는 정보서비스 시스템의 개발에 관련된 방법론으로 대상조직의 소프트웨어적 분석과 구성의 정의, 정보와 지식의 표현과 관리, 리소스 매칭기법 등을 기술하고, 이를 응용한 정보서비스 시스템을 구현하여 타당성을 보이고자 한다.

• Journal of Information Processing Systems
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• 제20권3호
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• pp.360-374
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• 2024

A personalized course recommendation algorithm based on deep learning in an online education cloud platform is proposed to address the challenges associated with effective information extraction and insufficient feature extraction. First, the user potential preferences are obtained through the course summary, course review information, user course history, and other data. Second, by embedding, the word vector is turned into a low-dimensional and dense real-valued vector, which is then fed into the compressed interaction network-deep neural network model. Finally, considering that learners and different interactive courses play different roles in the final recommendation and prediction results, an attention mechanism is introduced. The accuracy, recall rate, and F1 value of the proposed method are 0.851, 0.856, and 0.853, respectively, when the length of the recommendation list K is 35. Consequently, the proposed strategy outperforms the comparison model in terms of recommending customized course resources.

• 정보처리학회논문지B
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• 제19B권3호
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• pp.165-176
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• 2012

최근 사용자들이 생성한 콘텐츠들이 크게 늘어나고 커뮤니티 기반 웹 사이트가 발전함으로 인하여 사용자들에게 인터넷 자원을 추천하는 시스템이 큰 각광을 받고 있다. 그러나 대부분의 인터넷 자원 추천 시스템들은 사용자의 특징을 충분하게 반영하지 못하는 한계를 가지고 있다. 이에 따라 본 논문에서는 사용자의 특징이 충분히 반영되는 자원의 추천을 위하여 FOAF와 SNA를 사용한 추천 방법을 제안한다. 제안하는 방법은 1) FOAF를 통해 사용자의 특징 데이터와 태그 데이터를 취득한다. 2) 취득한 데이터를 세 종류의 행렬에 삽입하고 통합한 후 사용자, 사용자의 특징, 태그를 나타내는 그래프를 생성한다. 3) 소셜 네트워크 분석을 통해 추천 항목의 일반 특징과 핫태그(Hot tag)를 선정하여 인터넷 자원을 추천한다. 본 논문의 검증을 위하여 우리는 실험을 통해 본 논문에서 제안한 방법과 아이템 기반 추천 방법을 비교하였다. 이를 통해 보다 많은 사용자가 참여할수록 아이템 기반 추천 방법보다 본 논문에서 제안한 방법에 의한 추천 결과의 품질이 우수함을 확인하였다. 본 논문에서 제안하는 방법을 활용하면 사용자들에게 보다 적합한 자원을 추천하는 것이 가능하다. 그리고 제안하는 방법은 폭발적으로 늘어나는 인터넷 자원을 검색하는데 있어 효율적으로 활용될 수 있다.

• 한국안전학회지
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• 제30권3호
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• pp.135-140
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• 2015

Individuals who are vulnerable during disaster - including elderly, people with disabilities, children, pregnant women and etc - have a strong desire to protect themselves when disaster strikes since they are less capable to deal with the impact of disaster. Their experience and effort to keep them safe can be used as a resource to reduce the impacts of disaster not only for them but also for the community as a whole. Therefore, voluntary disaster management program will contribute to our society as a tool to respond effectively to disaster not only to meet the vulnerable's special needs but also to enhance community safety and public interest. This paper suggests a model that able "disaster vulnerable population" to take a leadership role in identifying risk and vulnerability factors, recommending disaster management strategy, and through that, contributing to enhance society's disaster plan. Therefore, this study aimed to surveyed individuals including "disaster vulnerable population" in order to assess the vulnerable's participation in disaster related volunteer work and surveyed associated institutions(volunteer centers, community centers) in order to research currently existing relevant programmes and the participation of "disaster vulnerable population" in such programmes. Also conducted focus group interview to explore voluntary program which will possibly integrate "disaster vulnerable population" into disaster management activities. As a result, three types of voluntary disaster management programs - education, public-relations, and activity - were suggested.

• Journal of Crop Science and Biotechnology
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• 제10권1호
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• pp.33-38
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• 2007

Nitrogen management at the panicle initiation stage(PI) should be fine-tuned for securing a concurrent high yield and high quality rice production. For calibration and testing of the recommendation models of N topdressing rates at PI for target grain yield and protein content of rice, three split-split-plot design experiments including five rice cultivars and various N rates were conducted at the experimental farm of Seoul National University, Korea from 2003 to 2005. Data from the first two years of experiments were used to calibrate models to predict grain yield and milled-rice protein content using shoot fresh weight(FW), chlorophyll meter value(SPAD), and the N topdressing rate(Npi) at PI by stepwise multiple regression. The calibrated models explained 85 and 87% of the variation in grain yield and protein content, respectively. The calibrated models were used to recommend Npi for the target protein content of 6.8%, with FW and SPAD measured for each plot in 2005. The recommended N rate treatment was characterized by an average protein content of 6.74%(similar to the target protein content), reduced the coefficient of variation in protein content to 2.5%(compared to 4.6% of the fixed rate treatment), and increased grain yield. In the recommended N rate treatments for the target protein content of 6.8%, grain yield was highly dependent on FW and SPAD at PI. In conclusion, the models for N topdressing rate recommendation at PI were successful under present experimental conditions. However, additional testing under more variable environmental conditions should be performed before universal application of such models.

• 산업경영시스템학회지
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• 제46권4호
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• pp.1-14
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• 2023

As markets and industries continue to evolve rapidly, technology opportunity discovery (TOD) has become critical to a firm's survival. From a common consensus that TOD based on a firm's capabilities is a valuable method for small and medium-sized enterprises (SMEs) and reduces the risk of failure in technology development, studies for TOD based on a firm's capabilities have been actively conducted. However, previous studies mainly focused on a firm's technological capabilities and rarely on business capabilities. Since discovered technologies can create market value when utilized in a firm's business, a firm's current business capabilities should be considered in discovering technology opportunities. In this context, this study proposes a TOD method that considers both a firm's business and technological capabilities. To this end, this study uses patent data, which represents the firm's technological capabilities, and trademark data, which represents the firm's business capabilities. The proposed method comprises four steps: 1) Constructing firm technology and business capability matrices using patent classification codes and trademark similarity group codes; 2) Transforming the capability matrices to preference matrices using the fuzzy function; 3) Identifying a target firm's candidate technology opportunities using the collaborative filtering algorithm; 4) Recommending technology opportunities using a portfolio map constructed based on technology similarity and applicability indices. A case study is conducted on a security firm to determine the validity of the proposed method. The proposed method can assist SMEs that face resource constraints in identifying technology opportunities. Further, it can be used by firms that do not possess patents since the proposed method uncovers technology opportunities based on business capabilities.