• Journal of Korean Library and Information Science Society
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• v.48 no.2
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• pp.215-236
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• 2017

The purpose of this study is to develop an automatic classification system for recommending appropriate books of 9 enneagram personality types, using book information data reviewed by librarians. Data used for this study are book review of 501 recommended titles for children and young adults from National Library for Children and Young Adults. This study is implemented on the assumption that most people prefer different types of books, depending on their preference or personality type. Performance test for two different types of machine learning models, nonlinear kernel and linear kernel, composed of 360 clustering models with 6 different types of index term weighting and feature selections, and 10 feature selection critical mass were experimented. It is appeared that LIBLINEAR has better performance than that of LibSVM(RBF kernel). Although the performance of the developed system in this study is relatively below expectations, and the high level of difficulty in personality type base classification take into consideration, it is meaningful as a result of early stage of the experiment.

• Journal of Information Science Theory and Practice
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• v.2 no.3
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• pp.55-65
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• 2014

This study investigated the information environment of lecturers in Federal Polytechnic, Offa, Kwara State, Nigeria, in relation to their information seeking behavior, extent of use of the polytechnic library, perceptions of the resources and services of the library, level of awareness and extent of use of the open access model of scholarly communications, as well as the challenges of accessing and using information resources. It adopted the survey research method, using a questionnaire for data collection, while the descriptive statistics method was used to analyse the data, using tabular presentation and simple percentages. From a population of 280 lecturers for the study, a purposive sample of 164 was drawn. The findings showed that the lecturers' information needs are focused on online use; they hardly use the polytechnic library due to their perceptions of the resources and services of the library. They are, to a greater extent, aware of open access initiatives, but do not publish in open access outlets, while various challenges affect their access and use of information resources for teaching and research. A recommendation was made, among others, that the polytechnic management should pay more critical attention to the library especially in the areas of adequate, current and comprehensive collections on all the programmes of the institution, as well as the provision of wireless internet services on the campus through a public-private partnership arrangement.

• International Journal of Knowledge Content Development & Technology
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• v.10 no.3
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• pp.69-86
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• 2020

As the South Korean government has recently announced its intention to implement a three-year policy on building additional libraries and complex community centers as the community-based everyday life SOC project, society has shed new light on libraries as public service institutions. Accordingly, this study was conducted to determine the factors affecting resident satisfaction with public libraries, intention to use, and intention to recommend public libraries, for use as basic data to increase resident satisfaction and use of public libraries in South Korea. To this end, we conducted a survey on residents who have experience with using 13 public libraries designated as regional representative libraries in South Korea. The surveyed data was verified with a structural equation using AMOS. The results were as follows. First, all factors, such as material, facility, staff, program, and service, except location and space, had a significant effect on resident satisfaction with public libraries. Second, it was found that satisfaction had a significant effect on the intention to use and intention to recommend. The results of this study may contribute to qualitatively improving public library services by reflecting the changing needs of users, as well as social trends at the working level of libraries in South Korean society.

• Journal of the Korean Society for information Management
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• v.25 no.3
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• pp.159-178
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• 2008

As social institution, the public libraries in changing social environment are required to adopt a more systematic and efficient managerial strategy, only to function properly and to achieve the given goal. In this context, the specialization of the public libraries means the provision of information and library services through differentiation and focus strategy, and should be realized for the efficient library management. In order to examine the specialization of the public libraries in Korea, this study builds the theoretical background of the specialization of the public libraries, looks into the current situation of the public libraries, investigates and analyzes the specialization of the public libraries in terms of information and library services, and suggests some recommendation for improvement. By so doing this study aims at enhancing our understanding of the specialization of the libraries as a whole.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.4
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• pp.35-55
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• 2018

The purpose of this study is to suggest how to activate the school library by examining how the users' perceive teacher librarians. For this purpose, questionnaires and in-depth interviews were conducted for students in 10 middle and high schools in Seoul and Gyeonggi. Analyses lead to these findings: the image types of teacher librarians were classified as professional image, active image, and simple-work image. Multiple regression analysis was used to examine the effect of teacher librarians images on school library user satisfaction. In order to enhance the teacher librarians images and school library user satisfaction, it is necessary to strive to cultivate the active attitude and professionalism of teacher librarians. Also, as the frequency of use is lower, the teacher librarians' images are viewed as simple work. Therefore, it is required to consider various reading events and reading education to raise the frequency of use. This study shows that the teacher librarians' images have a positive effect on school library users' satisfaction and suggests improvement plan for school library activation.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.4
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• pp.101-124
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• 2023

Book recommendations in libraries can be used as a tool to help users with vague needs browse and select books. Therefore, libraries spend a lot of time and effort to introduce various materials to their users and recommend suitable books. Meanwhile, various organizations other than libraries also publish recommended reading lists, and these lists reflect the intentions of the entity that selects the recommended books. The purpose of this study is finding out how the recommended book lists of libraries differ from the recommended reading lists of non-library organizations. To achieve this, the study limited the scope to 'teenagers', who are the main target audience for book recommendations in many organizations, and compared the recommended book lists of libraries and non-library organizations in terms of (1) the selection criteria for recommended books, (2) the characteristics of recommended books, and (3) the way of providing recommended book lists. Through this analysis, the study identified the characteristics and limitations of library recommended book lists and discussed areas for improvement.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.440-445
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• 2017

Due to the advance of e-commerce systems, the number of people using online shopping and products has significantly increased. Therefore, the need for an accurate recommendation system is becoming increasingly more important. Recurrent neural network is a deep-learning algorithm that utilizes sequential information in training. In this paper, an evaluation is performed on the application of recurrent neural networks to recommendation systems. We evaluated three recurrent algorithms (RNN, LSTM and GRU) and three optimal algorithms(Adagrad, RMSProp and Adam) which are commonly used. In the experiments, we used the TensorFlow open source library produced by Google and e-commerce session data from RecSys Challenge 2015. The results using the optimal hyperparameters found in this study are compared with those of RecSys Challenge 2015 participants.

• Journal of the Korean Society for information Management
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• v.38 no.2
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• pp.113-127
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• 2021

The purpose of this study is to propose a personalized book recommendation system to promote the use of university libraries. In particular, unlike many recommended services that are based on existing users' preferences, this study proposes a method that derive evaluation metrics using individual users' book rental history and tendencies, which can be an effective alternative when users' preferences are not available. This study suggests models using two matrix decomposition methods: Singular Value Decomposition(SVD) and Stochastic Gradient Descent(SGD) that recommend books to users in a way that yields an expected preference score for books that have not yet been read by them. In addition, the model was implemented using a user-based collaborative filtering algorithm by referring to book rental history of other users that have high similarities with the target user. Finally, user evaluation was conducted for the three models using the derived evaluation metrics. Each of the three models recommended five books to users who can either accept or reject the recommendations as the way to evaluate the models.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.17-22
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• 2021

In this paper, a machine learning-based automatic infographic recommendation system is proposed to improve the existing infographic production method. This system consists of a part that machine learning multiple infographic images and a part that automatically recommends infographics with artificial intelligence only by inputting basic data from the user. The recommended infographics are provided in the form of a library, and additional data can be input by drag & drop method. In addition, the infographic image is designed to be dynamically adjusted according to the size of the input data. As a result of analyzing the machine learning-based automatic infographic recommendation process, the matching success rate for layout and keyword was very high, and the matching success rate for type was rather low. In the future, a study to improve the matching success rate for the image type for each part of the infographic will be needed.

• Journal of Information Management
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• v.41 no.4
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• pp.227-249
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• 2010

Scholarly information has increased tremendously according to the development of IT, especially the Internet. However, simultaneously, people have to spend more time and exert more effort because of information overload. There have been many research efforts in the field of expert systems, data mining, and information retrieval, concerning a system that recommends user-expected information items through presumption. Recently, the hybrid system combining a content-based recommendation system and collaborative filtering or combining recommendation systems in other domains has been developed. In this paper we resolved the problem of the current recommendation system and suggested a new system combining collaborative filtering and Naive Bayes Classification. In this way, we resolved the over-specialization problem through collaborative filtering and lack of assessment information or recommendation of new contents through Naive Bayes Classification. For verification, we applied the new model in NDSL's paper service of KISTI, especially papers from journals about Sitology and Electronics, and witnessed high satisfaction from 4 experimental participants.