• Journal of Digital Convergence
• /
• v.19 no.5
• /
• pp.175-186
• /
• 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 Korea Entertainment Industry Association
• /
• v.15 no.6
• /
• pp.23-33
• /
• 2021

Under the long-term influence of COVID-19, offline activities were interrupted and online communication became the main way. With the rapid development of Korean Wave and network information technology, there have been many entertainment communication platforms. Fans can communicate with stars and other fans and share information through entertainment and communication platforms. This can improve users' perception of the value of entertainment communication platforms, arouse emotional resonance and have a positive impact on users' platform recommendation intention. In this study, the influence of user interaction, identity and recommendation intention of entertainment communication platforms was investigated by questionnaire. The results are as follows: First, the interaction between fans and content has a positive effect on psychological and behavioral identity. Second, the interaction between fans does not affect their psychological and behavioral identity. Third, the interaction between fans and stars has a positive impact on psychological identity and behavior identity. Fourth, psychological identity and behavioral identity have a positive impact on community members' willingness to recommend. Behavioral identity plays a partial mediating role between psychological identity and recommendation intention. Based on the above analysis results, the present situation, limitations and future research directions of this study are put forward.

• Culinary science and hospitality research
• /
• v.22 no.4
• /
• pp.181-191
• /
• 2016

This study examined the factors that affect the relationship between eco-friendly agricultural products selection criteria, consumer trust, and recommendation intention. A total of 220 questionnaires were distributed to consumers, of which 210 were deemed suitable for analysis after the removal of 10 unusable responses. In order to perform statistical analyses required in the study, SPSS 18.0 Statistical Program was employed for frequency analysis, factor analysis, reliability analysis, correlations, and regression analysis. The results of exploratory factor analysis showed that four factors regarding eco-friendly agricultural products were extracted from all measurements with a KMO of 0.735 and a total cumulative variance of 79.373%, With regard to consumer trust, one factor was extracted with a total cumulative variance of 75.431% and a KMO score of 0.695. One factor for recommendation intention was extracted that accounted for a total cumulative variance of 68.428% and a KMO score of 0.694. All factors were significant to .000 and the correlation between variables was significant. Thus, based on the results, the main research hypotheses that identify the relationships between selection criteria, consumer trust and recommendation retention were adopted.

• Journal of the Korean Society for information Management
• /
• v.24 no.3
• /
• pp.43-65
• /
• 2007

Automatic recommendation system of panel pool should be designed to support universal, expertness, fairness, and reasonableness in the process of review of proposals. In this research, we apply the theory of probabilistic ontology to measure relatedness between terms in the classification of academic domain, enlarge the number of review candidates, and rank recommendable reviewers according to their expertness. In addition, we construct a researcher network connecting among researchers according to their various relationships like mentor, coauthor, and cooperative research. We use the researcher network to exclude inappropriate reviewers and support fairness of reviewer recommendation process. Our methodology recommending proper reviewers is verified from experts in the field of proposal examination. It propose the proper method for developing a resonable reviewer recommendation system.

• Journal of the Korean Society for information Management
• /
• v.30 no.2
• /
• pp.297-315
• /
• 2013

This study aims to analyze and evaluate term suggestion services of major search portals, Naver and Google Korea. In particular, this study evaluated relevance and currency of related search terms provided, and analyzed characteristics such as number and distribution of terms, and queries that did not produce terms. This study also analyzed types of terms in terms of the relationship between queries and terms, and investigated types and characteristics of harmful terms and terms with grammatical errors. Finally, Korean queries and English queries, and popular queries and academic queries were compared in terms of the amount and relevance of search terms provided. The results of this study show that the relevance and currency of Naver's related search terms are somewhat higher than those of Google. Both Naver and Google tend to add terms to or delete terms from original queries, and provide identical search terms or synonym terms rather than providing entirely new search terms. The results of this study can be implemented to the portal's effective development of term suggestion services.

• The Journal of Society for e-Business Studies
• /
• v.12 no.1
• /
• pp.99-122
• /
• 2007

The rule based system is inference engine which can correspond quickly to new business model change and improvement requirement by dealing with the business know-how and expert knowledge as well as business process of enterprise and has been trying to apply to the various industries. As a part of application cases for rule-based system, we develop and implement the rule-based insurance product recommend and design system for the efficient decision making of insurance product in insurance industry which is sensitively affected by needs of customers, various kinds of product, and environment changes. The process of fuzzy inference of the developed system helps to recommend and design the proper Insurance product using the information of the present customer and the previous members. This approach is expected that it will be the core technology for the recommendation and design of the tailored insurance product by deciding and corresponding needs of various kinds of customer quickly in future insurance industry.

• Culinary science and hospitality research
• /
• v.22 no.5
• /
• pp.252-266
• /
• 2016

The purpose of this study is to verify a relationship among service quality and customer satisfaction of wedding hall restaurants, and recommendation intention, as well as the moderating effect of image of wedding halls and hotels on the relationship. A hierarchical regression analysis thorugh SPSS was conducted to test the model hypotheses. Research samples were collected from 331 customers of wedding hall restaurants and hotels located in Seoul. The findings and implications of the research can be summarized as follows. First, the employees, facilities and environment service, and convenience of wedding hall restaurants had a positive effect on customer satisfaction of wedding hall restaurants. Second, evidence suggested that service quality of wedding hall restaurants had a positive effect on recommendation intention. Third, while there was a negative moderating effect of image of wedding halls and hotels between food and employee service quality and customer satisfaction, a positive moderation effect of image of wedding halls and hotels was found. Fourth, there was a negative moderating effect between customer satisfaction and recommendation intention.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.4
• /
• pp.286-291
• /
• 2020

In this paper, we propose a system that recommends music through tempo-oriented music classification and sensor-based human activity recognition. The proposed method indexes music files using tempo-oriented music classification and recommends suitable music according to the recognized user's activity. For accurate music classification, a dynamic classification based on a modulation spectrum and a sequence classification based on a Mel-spectrogram are used in combination. In addition, simple accelerometer and gyroscope sensor data of the smartphone are applied to deep spiking neural networks to improve activity recognition performance. Finally, music recommendation is performed through a mapping table considering the relationship between the recognized activity and the indexed music file. The experimental results show that the proposed system is suitable for use in any practical mobile device with a music player.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.3
• /
• pp.67-72
• /
• 2021

Association rule mining is a method of showing the relationship between patterns hidden in several tables. These days, granulation logic is used to add more detailed meaning to association rule mining. In addition, unlike the existing system that recommends using existing data, the granulation related rules can also recommend new subscribers or new products. Therefore, determining the qualitative size of the granulation of the association rule determines the performance of the recommendation system. In this paper, we propose a granulation method for subscribers and movie data using fuzzy logic and Shannon entropy concepts in order to understand the relationship to the movie evaluated by the viewers. The research is composed of two stages: 1) Identifying the size of granulation of data, which plays a decisive role in the implications of the association rules between viewers and movies; 2) Mining the association rules between viewers and movies using these granulations. We preprocessed Netflix's MovieLens data. The results of meanings of association rules and accuracy of recommendation are suggested with managerial implications in conclusion section.

• Journal of Intelligence and Information Systems
• /
• v.28 no.4
• /
• pp.287-308
• /
• 2022

The explosive growth of cryptocurrency, led by Bitcoin has emerged as a major issue in the financial market recently. As a result, interest in cryptocurrency investment is increasing, but the market opens 24 hours and 365 days a year, price volatility, and exponentially increasing number of cryptocurrencies are provided as risks to cryptocurrency investors. For that reasons, It is raising the need for research to reduct investors' risks by dividing cryptocurrency which is not suitable for recommendation. Unlike the previous studies of maximizing returns by simply predicting the future of cryptocurrency prices or constructing cryptocurrency portfolios by focusing on returns, this paper reflects the tendencies of investors and presents an appropriate recommendation method with interpretation that can reduct investors' risks by selecting suitable Altcoins which are recommended using Apriori algorithm, one of the machine learning techniques, but based on the similarity and association rules of Bitocoin.