• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.27-29
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• 2015

최근 IT기술의 발달로 인하여 다양한 분야에서 IT기술을 활용한 융합기술의 시도가 많아지고 있다. 특히 인터넷의 발달과 전자책(e-Book) 시장규모가 커짐에 따라 도서에 대한 정보가 많아지고 있으며, 이러한 정보를 분석하여 활용하는 서비스 시스템에 대한 관심이 높아지고 있다. 하지만 현재 서비스되고 있는 대부분의 온라인 서점에서는 도서의 기본 서지정보와 같이 도서 본문 내용과는 무관한 출판사나 서점에서 도서를 관리하기 위한 정보만을 제공하고 있으며, 도서에 대한 다양한 정보를 활용한 키워드 추출 및 장르 분류를 통한 검색의 효율성 제공이 미흡한 현실이다. 본 논문에서는 도서의 본문 텍스트 정보를 마이닝 처리하여 도서 페이지의 흐름에 따라 포함되어있는 장르를 분류하고 이에 대한 결과를 사용자에게 친화적인 시각화 기법으로 제공되는 시스템을 설계하고 구축하였다. 제안한 서비스 시스템은 의미 분석을 기반으로 도서 정보의 구체적, 실제적, 직관적 정보를 제공하여 도서 추천 서비스에 활용될 것이다.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.311-336
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• 2022

This study analyzed the contents of Goodreads review data, which is a social cataloging service with the participation of book users around the world, to identify the preference factors that affect book users' book recommendations in the library information service environment. To understand user preferences from a more detailed point of view, sub-datasets for each rating group, each book, and each user were constructed in the sample selection process. Stratified sampling was also performed based on the result of topic modeling of review text data to include various topics. As a result, a total of 90 preference factors belonging to 7 categories('Content', 'Character', 'Writing', 'Reading', 'Author', 'Story', 'Form') were identified. Also, the general preference factors revealed according to the ratings, as well as the patterns of preference factors revealed in books and users with clear likes and dislikes were identified. The results of this study are expected to contribute to more sophisticated recommendations in future recommendation systems by identifying specific aspects of user preference factors.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.175-186
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• 2021

The roles and functions of domestic public libraries are diversifying, but various problems have emerged due to internally biased book lending. In addition, due to the 4th Industrial Revolution, public libraries have introduced a book recommendation system focusing on popular books, but the variety of books that users can access is limited. Therefore, in this study, the public library unborrowed book recommendation system was implemented limiting its spatial scope to Duryu Library in Daegu City to enhance the satisfaction of public library users, by using the loan records data (213,093 cases), user information (35,561 people), etc. and utilizing methods like cluster analysis, topic modeling, content-based filtering recommendation algorithm, and conducted a survey on actual users' satisfaction to present the possibility and implications of the unborrowed book recommendation system. As a result of the analysis, the majority of users responded with high satisfaction, and was able to find the satisfaction was relatively high in the class classified by specific gender, age, occupation, and usual reading. Through the results of this study, it is expected that some problems such as biased book lending and reduced operational efficiency of public libraries can be improved, and limitations of the study was also presented.

• 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.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.1067-1069
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• 2013

전자상거래 시장의 급격한 성장에 따라 고객이 원하는 정보를 얻기 위해 소요되는 시간과 노력을 절약하기 위한 방안으로 추천 시스템의 필요성이 강조되고 있다. 추천 시스템에 일반적으로 가장 많이 쓰이는 것이 협업필터링 기법이다. 협업 필터링은 추천시스템 분야에서 가장 성공적인 기법으로 전자상거래 포털에서 가장 널리 이용되고 있다. 그러나 희박성, 확장성, 투명성 등의 문제점을 가진다. 본 논문에서는 프로파일링 기법을 사용해 협업필터링의 희박성 문제 해소 방안으로 개인성향을 이용하여, 보다 정확한 추천을 하여 온라인 서점에 적용할 수 있는 추천 시스템이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.466-469
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• 2021

최근 자연어 처리에 대한 관심이 증가함에 따라 자연어 처리 기술을 활용한 다양한 추천 시스템이 등장하고 있다. 본 논문에서는 자연어 처리를 이용한 서비스를 개발한다. 본 논문에서 개발한 서비스는 KoNLPy 와 Word2Vec 을 이용하여 크라우드 펀딩 프로젝트 창작자 및 후원자에게 키워드 및 키워드와 유사한 단어가 제목에 포함되는 프로젝트를 추천해준다. 단문 텍스트로서 프로젝트 제목을 사용하여 데이터를 자연어 처리 한 후, 딥러닝 모델에 적용시켜 추출한 데이터를 기반으로 창작자와 후원자에게 추천해주는 방식이다. 따라서 본 서비스는 프로젝트 제목 정보를 통한 추천 시스템의 개발로, 나아가 영화, 도서와 같은 콘텐츠 추천 분야에도 적용할 수 있을 것으로 기대한다.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.311-334
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• 2021

The purpose of this study is to present the theoretical basis and quantified objective standards for the establishment of collection management policy. The study results are summarized as follows. Most of the study books were in the form of periodicals as a steady seller. Most of the steady sellers were textbooks which published periodically. As a modern novel, a steady seller was able to confirm the phenomenon of dependence on a specific author. Bestsellers were investigated to be influenced by publishers and authors. Books of publishers that publish comics and children's textbooks had a significant correlation with the selection of bestsellers. The average number of recommended books borrowed per recommended book was 14,871. The average number of loans per book selected as a bestseller was 53,531. Based on the loan data, about 80-82% of all top-tier loans were covered by 90%, and about 27-29% of all top-ranked loans were covered by 50%. This shows that the Pareto Principle can be firmly applied to public library lending patterns. Loans in the field of literature accounted for 50.6% of the total loans. Among literature, Korean literature accounted for 51.3% of the total. The natural sciences were generating more loans with a relatively small pool of literature compared to other subject fields.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.3
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• pp.241-266
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• 2010

The purpose of this study is to examine the current state of webzine publications in Korean university libraries. We assess the menu, composition and contents of various types of webzines at thirty six different Korean university libraries. Highlights of our survey include the following: 1) Most university libraries operate several different webzine sites. 2) Categories included in library webzines mainly include 'Notices', 'Academic Database Information', 'Current Books', 'Recommended Reading', 'Utilization of Information', 'Book Review', 'Tips for Using the Library', 'Special Issues', 'Service Information', 'Quiz', 'Column', 'Special Events'. 3) Of these, the most popular categories were: 'Notices', 'Service Information', 'Tips for Using the Library', 'Special Issues', and 'Recommended Reading'.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.2
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• pp.109-114
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• 2002

E-commerce customers can reduce purchasing cost by the help of comparison shopping agents that collect price information of products in the shopping malls. However, user expects a software agent that can recommend product information satisfying various purchase conditions besides price. In this paper, we present a MAS (multi-agent system) which retrieves and recommends book information suitable for various user needs to realize an agent-based E-Commerce. We implemented and tested our MAS to help on-line bookstore customers. From the results, we could provide E-commerce customers various book purchase conditions for several online bookstores in real-time.

• Journal of Korean Library and Information Science Society
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• v.52 no.4
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• pp.205-228
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• 2021

This study focuses on the development of checklist on articulating reading appreciation, which will be used as the initial data for book recommendation for library users. As reading comprehension is prerequisite for reading appreciation, researchers analyzed research articles on reading comprehension to find out the core factors on reading comprehension and categorize them. Studies on reader response theory and literacy education were also examined: key words and phrases that will stimulate readers' response to reading were extracted and formed as questions. These questions were reviewed by experts on reading education. The final checklist consists of 14 questions - 4 questions on literal·inferential comprehension, 3 on evaluative comprehension, and 3 on appreciative comprehension.