• Journal of the Korean BIBLIA Society for library and Information Science
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• v.31 no.4
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• pp.95-119
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• 2020

The study examined the behavior of infant's caregivers using public libraries, measured the level of awareness of infant and toddler services in the library to determine the factors affecting their revisit or recommendation of use to others, and examined the impact of such recognition on the use behavior, revisit and willingness to recommend others. The study surveyed 146 caregivers of infants who use four public libraries in Gwangju Metropolitan City on demographic characteristics, library use behavior, level of awareness of library services, library revisit and recommendation to others. Analysis of this survey shows that the factors that influence the caregivers' revisit of the library or their desire to recommend to others through their caregivers' use of the library are the factors that influence the expansion of information data, the stability of space facilities, the accessibility of space facilities, and the ease of participation in programs among the various service factors provided by the library rather than the personal factors of infants and toddlers' caregivers.

• Proceedings of the Korean Society for Information Management Conference
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• 2014.08a
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• pp.131-134
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• 2014

전 세계적으로 다양한 영역에서 빅데이터 활용 성공 사례가 증가하게 되면서 도서관 분야에서도 빅데이터를 활용한 신규 서비스 개발 필요성이 제기 되고 있다. 본 연구는 공공도서관의 정보서비스 제공 및 도서관 운영 실태, 이용자 특성 등을 분석하였고, 이를 바탕으로 새로운 도서관 패러다임을 이끄는 도서관 빅데이터 서비스 모형을 개발하고자 한다. 먼저, 설문 대상을 사서 집단과 이용자 집단으로 나누어 공공도서관 이용현황을 파악하였고, 대표적인 공공도서관 서비스인 장서개발 및 열람봉사, 이용자 맞춤형 추천서비스에 대한 수요도를 분석하였다. 추가적으로 응답에 대한 집단 간 차이에 대해 살펴보았다. 분석결과를 토대로 관련 서비스 개발을 위한 방향성을 도출하였고, 향후 활용 가능한 도서관 빅데이터 서비스 정립을 위한 기초 방안을 제시하였다.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.4
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• pp.147-167
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• 2020

The purpose of this study is to analyze the factors influencing the intention of revisiting and recommending by applying a structural equation model, targeting the service quality factors of university libraries derived from previous studies. For 11 days from April 30th, 2020 to May 10th, 2020, a total of 127 user groups (undergraduate students, graduate students, professors/instructors) were surveyed on their intention to revisit and recommend. The analysis results are as follows. 'Materials' and 'service customization' were shown as quality dimensions that influence revisit. In addition, revisiting was found to have an effect on recommendation intention, and it was analyzed that 'materials' and 'service customization' affect not only revisit but also recommendation intention. In addition, 'service customization' was found to be a factor that directly affects the intention to recommend. Based on this, a method of applying the concept of customization to library services and marketing was proposed in an environment where users' needs are diversifying and becoming personalized.

• Journal of Korean Library and Information Science Society
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• v.53 no.4
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• pp.189-209
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• 2022

The purpose of this study is to analyze the content of the online book curation services and recommended books list by public libraries in Korea and to identify their properties. The case for analysis is a list of 11,447 recommended books provided by 35 online book curation services collected from 23 public libraries and the main results of the study are as follows. Only few case libraries were presenting recommendation themes, and recommendation targets were most often not specific, and the recommendation cycle of books was the most monthly. In general, books recommended for book curation do not overlap with each other, but there was overlap in the field of literature (novels) published in 2019~2021. For recommended books, the proportion of books published by some publishers was high, and books published in 2019~2021 were the most common. The subject areas analyzed based on the KDC 6th ed were literature the most. Readers analyzed by ISBN were of in the order of cultural books and children's books, and the type of publication was in the order of books, pucture books, and comics. Based on these research results, it was required to develop guidelines for online book curation service for public libraries and build a platform to share with libraries.

• Journal of Korean Library and Information Science Society
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• v.47 no.1
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• pp.279-303
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• 2016

This study proposes the Book-Curation service as part of the information service offered through school library websites. Also, this study aims to establish recommendation standards for curation prior to detailed system planning. For such service, the following tasks were carried out. First, the list of recommended books of existing systems were analyzed to identify the attributes that can be used for recommendation in the user and book information. Second, the analyzed attributes were utilized to establish 12 recommendation standards. Finally, a survey was carried out to identify the user preferences as to each standards. The results are as follows. First, the majority of students responded that curation service is necessary for using a library. Second, the top three standards are as follows: "best lending books based on the keywords of individual users"; "best lending books of the same year students"; "best lending books on the textbook-related reference booklist".

• 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 Korean Library and Information Science Society
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• v.52 no.1
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• pp.155-178
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• 2021

In the era of the 4th industrial revolution, public libraries need a strategy for promoting intelligent library services in order to actively respond to changes in the external environment such as artificial intelligence. Therefore, in this study, based on the concept of artificial intelligence and analysis of domestic and foreign artificial intelligence related trends, policies, and cases, we proposed the future direction of introduction and development of artificial intelligence services in the library. Currently, the library operates a reference information service that automatically provides answers through the introduction of artificial intelligence technologies such as deep learning and natural language processing, and develops a big data-based AI book recommendation and automatic book inspection system to increase business utilization and provide customized services for users. Has been provided. In the field of companies and industries, regardless of domestic and overseas, we are developing and servicing technologies based on autonomous driving using artificial intelligence, personal customization, etc., and providing optimal results by self-learning information using deep learning. It is developed in the form of an equation. Accordingly, in the future, libraries will utilize artificial intelligence to recommend personalized books based on the user's usage records, recommend reading and culture programs, and introduce real-time delivery services through transport methods such as autonomous drones and cars in the case of book delivery service. Service development should be promoted.

• Journal of Korean Library and Information Science Society
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• v.52 no.3
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• pp.287-311
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• 2021

It is not easy for information users to find books that are suitable for them in a knowledge information society. There is a growing need for libraries to break away from traditional services and provide user-tailored recommendation services, but there are few qualitative studies on user satisfaction so far. In this study, a user-customized book recommendation was performed by applying Apriori, a correlation analysis algorithm, and satisfaction factors were analyzed in depth through interviews. The experimental data was the loan data of 100 people who used the most frequently used loan data for 10 years from 2009 to 2019 of the S library in Seoul. The interviewees of the experiment were those who could be interviewed in depth. After the correlation analysis, the concepts and categories derived by analyzing the interview data were 59 concepts, 6 sub-categories, and 2 upper categories, respectively. The upper categories were 'reading' and 'book recommendation service'. In the 'reading' category, there were 16 concepts of motivation for reading, 8 concepts of preferred books, and 12 concepts of expected effects. Also, in the category of 'reading recommendation service', there were 10 'reflection factors', 4 'reflection methods', and 9 'satisfaction factors'.

• KSLA Bulletin
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• s.9
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• pp.53-64
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• 2018

• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.10-19
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• 2010

The progress of computers and Web has given rise to a rapid increase of the quantity of the useful information, which is making the demand of recommender systems widely expanding. Like in other domains, a recommender system in a digital library is important, but there are only a few studies about the recommender system of research papers, Moreover none is there in korea to our knowledge. In the paper, we seek for a way to develop the NDSL recommender system of research papers based on the survey of related studies. We conclude that NDSL needs to modify the way to collect user's interests from explicit to implicit method, and to use user-based and memory-based collaborative filtering mixed with contents-based filtering(CF). We also suggest the method to mix two filterings and the use of personal ontology to improve user satisfaction.