• Journal of Korean Library and Information Science Society
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• v.54 no.4
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• pp.255-279
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• 2023

The purpose of this study is to derive implications through a comparison of the current status of catalog enriched content services provision in U.S. public libraries and domestic public libraries. In addition, we are seeking ways to improve the catalog enriched content services for domestic public libraries in the future. From early September to mid-October 2023, specific books were searched on public library websites in the U.S. and Korea, and the functions of the enriched content services shown in the search results were compared. The results are as follows: First, domestic public library enriched content services require a separate company to develop and provide an enriched content services solution. Second, the enriched content services platform must discover domestic information sources that can be utilized in the areas of book-centered, book recommendation, and community engagement. Third, it is necessary to develop enriched content using public data such as the Library Information Naru. Fourth, each integrated library must that data generated from local community engagement services can be utilized as an enriced content service.

• Journal of Korean Library and Information Science Society
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• v.43 no.4
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• pp.161-181
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• 2012

Because of the development of varieties multimedia and information technology, university students's book reading and university library's book borrowing rate is decreasing. As a center of liberal learning, university libraries have many events for the promotion of reading. But those events do not give practical help for students. In order to solve this problem, researcher benchmarked 4 university libraries that have most active in reading events. The results is below. For reading promotion about the liberal books that was recommended by university, it is suitable to be reading in university education system. Reading discussion is effective for motivation in library reading events. Writing is preferable at reading education by integrating the personal and reading experience. The reading ability of librarians is essential for good reading service in library.

• Journal of Korean Library and Information Science Society
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• v.49 no.4
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• pp.265-294
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• 2018

Nowadays, due to an explosive increase in information, information filtering is very important to provide proper information for users. Users hardly obtain scholarly information from a huge amount of information in NDSL of KISTI, except for simple search. In this paper, we propose the service, PIN to solve this problem. Pin provides the word cloud including analyzed users' and others' interesting, co-occurence, and searched keywords, rather than the existing word cloud simply consisting of all keywords and so offers user-customized papers, reports, patents, and trends. In addition, PIN gives the paper classification in NDSL according to keyword matching based classification with the overlapping classification enabled-academic classification system for better search and access to solve this problem. In this paper, Keywords are extracted according to the classification from papers published in Korean journals in 2016 to design classification model and we verify this model.

• Journal of Korean Library and Information Science Society
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• v.53 no.1
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• pp.231-263
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• 2022

The understanding and capability to utilize artificial intelligence (AI) incorporated technology has become a required basic skillset for the people living in today's information age, and various members of the university have also increasingly become aware of the need for AI education. Amidst such shifting societal demands, both domestic and international university libraries have recognized the users' need for educational content centered on AI, but a user-centered service that aims to provide personalized recommendations of digital AI educational content is yet to become available. It is critical while the demand for AI education amongst university students is progressively growing that university libraries acquire a clear understanding of user intention towards an AI educational content recommender system and the potential factors contributing to its success. This study intended to ascertain the factors affecting acceptance of such system, using the Extended Technology Acceptance Model with added variables - innovativeness, self-efficacy, social influence, system quality and task-technology fit - in addition to perceived usefulness, perceived ease of use, and intention to use. Quantitative research was conducted via online research surveys for university students, and quantitative research was conducted through written interviews of university librarians. Results show that all groups, regardless of gender, year, or major, have the intention to use the AI-related Educational Content Recommendation System, with the task suitability factor being the most dominant variant to affect use intention. University librarians have also expressed agreement about the necessity of the recommendation system, and presented budget and content quality issues as realistic restrictions of the aforementioned system.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.129-139
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• 2012

This paper introduces a recommender system that is to recommend broadcast content. Our recommender system uses user's viewing history for personalized recommendations. Broadcast contents has unique characteristics as compared with books, musics and movies. There are two types of broadcast content, a series program and an episode program. The series program is comprised of several programs that deal with the same topic or story. Meanwhile, the episode program covers a variety of topics. Each program of those has different topic in general. Therefore, our recommender system recommends TV programs to users according to the type of broadcast content. The recommendations in this system are based on user's viewing history that is used to calculate content similarity between contents. Content similarity is calculated by exploiting collaborative filtering algorithm. Our recommender system uses java sparse array structure and performs memory-based processing. And then the results of processing are stored as an index structure. Our recommender system provides recommendation items through OPEN APIs that utilize the HTTP Protocol. Finally, this paper introduces the implementation of our recommender system and our web demo.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.280-282
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• 2001

인터넷의 발달로 웹에서 제공되는 정보와 서비스의 양이 폭발적으로 증가하고 있다. 따라서 사용자들은 보다 쉽게 빠르게 정보를 찾을 수 있도록 지원해 주는 정보 검색 에이전트에 대한 개발을 요구하고 있다. 본 논문에서는 사용자에게 적합한 도서 정보를 검색 및 추천하는 멀티 에이전트 시스템을 설계한다. 그리고 여러 에이전트 사이의 행동을 제어하는 CA(Coordination Agent) 에이전트의 조정 기능과 각 에이전트간의 통신을 지원하는 KQML처리의 알고리즘을 구현한다. 구현 결과 CA의 Message Queue 비교를 토한 조정 기능은 IEA(Information Extraction Agent)의 중복된 정보검색을 방지하여 보다 빠르고 효율적인 정보 검색의 효과를 얻을 수 있었고, KQML은 JAVA의 클래스로 구현하여 본 시스템에서 사용된 메시지 이외의 모든 KQML 메시지 처리 기능을 포함할 수 있도록 하였다.

• Journal of Korean Library and Information Science Society
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• v.41 no.1
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• pp.149-165
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• 2010

In this research, we analyze about the general service provided by Society of Korean journal articles of science and technology. Personalized retrieval services which are suitable to the articles service were developed based on this. That is, there are personalized retrieval system based on user's keyword, authors navigation system, automatic topic recommendation system based on author's keyword, and similar user automatic recommendation system. In this research, personalized service methods being suitable to the articles service of Society tries to be considered through the user survey.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.95-115
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• 2022

The purpose of this study is to transform the sub-categorization terms of the National Science and Technology Standards Classification System into technical keywords by applying a machine learning algorithm. For this purpose, AttentionMeSH was used as a learning algorithm suitable for topic word recommendation. For source data, four-year research status files from 2017 to 2020, refined by the Korea Institute of Science and Technology Planning and Evaluation, were used. For learning, four attributes that well express the research content were used: task name, research goal, research abstract, and expected effect. As a result, it was confirmed that the result of MiF 0.6377 was derived when the threshold was 0.5. In order to utilize machine learning in actual work in the future and to secure technical keywords, it is expected that it will be necessary to establish a term management system and secure data of various attributes.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.30 no.3
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• pp.223-244
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• 2019

This study aims to propose educational information services for social science teachers by analyzing their information seeking behaviors. The author carried out in-depth interviews with thirteen social science teachers in Daejeon and analyzed them using an information seeking behavior model of Leckie, Pettigrew and Sylvain. The study results showed that information needs of social science teachers arise from extrinsic and intrinsic motivations according to their work roles and tasks. Also, the characteristics of information needs such as repeatability, predictability, urgency, and complexity appear to influence information seeking behaviors. The participants used various information sources including web, book, and interpersonal sources. Moreover, the study observed some factors that may influence perception toward information sources such as trustworthiness, information quality, packaging, prior success experience. Finally, the perception change and use frequency of information sources were also identified. Based on these findings, the author proposed information services for social science teachers including integrated information provision services, information literacy programs, networking services and readers advisory services.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.4
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• pp.105-123
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• 2016

This study analyzes the spectrum of recommended books for adults included in the bibliotherapy book lists commonly used in libraries and organizations in the UK, US, and Korea. While the recommended book lists in the UK and US retain a diverse range of books relevant to the practitioners' needs, the Korean bibliotherapy book lists are mostly made up of non-fiction self-help books regardless of where the bibliotherapy service is provided. In the subcategory of the bibliotherapy book lists in the UK and US, aside from fictions, books on "health, fitness, dieting" including medical books rank higher than any other kind, which shows that bibliotherapy claims to have therapeutic effects in those organizations. In Korean bibliotherapy book lists, on the other hand, so-called "psychology books impregnated with self-help ideology" take up more than 60%. With the prospect of bibliotherapy as an interdisciplinary practice in mind, I suggest that bibliotherapy should draw upon the insights from humanities in order to help participants have time for deep introspection and attain inner maturity rather than just try to restore their normal conditions before the crisis.