• Genomics & Informatics
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• v.2 no.3
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• pp.142-146
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• 2004

Biological data and analysis tools are accumulated in distributed databases and web servers. For this reason, biologists who want to find information from the web should be aware of the various kinds of resources where it is located and how it is retrieved. Integrating the data from heterogeneous biological resources will enable biologists to discover new knowledge across the specific domain boundaries from sequences to expression, structure, and pathway. And inevitably biological databases contain noisy data. Therefore, consensus among databases will confirm the reliability of its contents. We have developed WeSAT that integrates distributed and heterogeneous biological databases and analysis tools, providing through Web Services protocols. In WeSAT, biologists are retrieved specific entries in SWISS-PROT/EMBL, PDB, and KEGG, which have annotated information about sequence, structure, and pathway. And further analysis is carried by integrated services for example homology search and multiple alignments. WeSAT makes it possible to retrieve real time updated data and analysis from the scattered databases in a single platform through Web Services.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• Journal of Korean Society of Archives and Records Management
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• v.3 no.2
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• pp.34-51
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• 2003

The purposes of this study are to categorize the archival body of knowledge based on the analysis of two guidelines and websites of 10 archival graduate programs in the United States, and to make suggestions for the development of archival education in Korea. Basic knowledge, core knowledge, complementary knowledge, practical knowledge, and research knowledge are found as components of the archival body of knowledge. The basic knowledge is the ability to understand general circumstances related to records and archives. The core one is to master the required competence as archivists. The complementary one is to understand other disciplinary backgrounds and their various research methods. The practical one is to be obtained from field experiences and the research one is to make a scholastic contribution through a deep research process. Curriculum development for preservation, electronic records management, use of computer technologies, archival services and advocacy, more interdisciplinary courses and internship programs are suggested as important factors for the future archival education. And cooperative research and appointment of more faculty members are also suggested. Finally, the development of guideline for Korean archival graduate programs are strongly suggested.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.9
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• pp.647-658
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• 2018

Modern society is complex and rapidly changing, and knowledge sharing is needed to acquire and create knowledge. Knowledge sharing is the act of providing information knowledge and know-how of their own in order to cooperate with or help their colleagues. This study presents a research model using social capital theory to explain the mobile knowledge sharing behavior of virtual community members. Based on previous studies, social capital theory is divided into structural, relational, and cognitive aspects. It was composed of social interaction ties as a measure of structural aspect, trust as a measure of cognitive aspect, shared language, shared vision and relational aspect. After collecting survey data, factor analysis and regression analysis were performed using SPSS 22. In this way, we examined how the detailed factors of social capital affect information sharing behavior and how the level of knowledge sharing affects community promotion. The results showed that social interaction ties, shared language, shared vision, and trust affect knowledge sharing. Knowledge sharing has had a positive impact on community promotion.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.197-211
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• 2021

The emergence of knowledge-sharing live streamers provides more diversified content to the live streaming platform. Analysis of the factors affecting the intention to use knowledge sharing live streaming users can allow the live streaming platform to understand better the adoption characteristics of users who follow this type of content. Help platform operators provide better services and help live streaming platforms innovate. Based on the TAM model, this research uses questionnaire surveys and structural equation models to construct a conceptual model of the influencing factors of users' intentions in the knowledge sharing live streaming and conduct an empirical analysis on the influencing factor models. The results of data analysis show that a significant influence of users' attitudes of knowledge sharing live streaming is perceived usefulness, followed by flow experience; perceived value has a positive impact on users' attitudes and intention to use, and the positive influence of users attitude significantly affect the user's intention.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.81-96
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• 2006

Changes in document delivery service environment such as spread of web-based research information communication and direct communication between users and information providers have considerable effects on document delivery service institutes. Swift advances in information technology have allowed users to receive information on their desktops via web. Web-based document delivery makes the massive scale of reproduction and distribution possible so it needs to protect the copyright holders' rights. This study identifies the current trends and issues of document delivery service environment and reviews electronic document delivery services of foreign countries. Also this study introduces the domestic electronic document delivery service, e-DDS, and evaluates the copyright issues for the service.

• The Korean Journal of Emergency Medical Services
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• v.7 no.1
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• pp.81-94
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• 2003

This study tries to examine the level of safety consciousness and first aid knowledge of 124 college students who attend non-public health departments in Gwangju from April 1 to 30, 2003 and apply the results of the study to curriculum. The results of this study are as follows; 1. On experiences of need of first-aid, 87.5% of respondents said 'yes' and there was a significant difference in the number of their siblings($x^2$ = 7.482, p = .048). 2. Sources of education of first aid were mostly at school(46.8%), no education(23.4%), through mass communication(22.6%) and by themselves(7.3%). There were significant differences by characteristics in sex($x^2$ = 30.230, p = .000), year($x^2$ = 10.821, p = .013) and mother's education($x^2$ = 18.932, p = .025). 3. Sources of information of first aid were mostly through TV(46.8%), followed by others (42.7%), newspapers(7.3%) and magazines(3.2%). 4. On the opinions of the most suitable period for educating first aid, elementary school was highest(41.9%), followed by kindergarten(29.0%), middle school(21.0%) and high school (8.1%) and there were significant difference by characteristics of subjects in sex($x^2$=9.689, p= .021) and year($x^2$=19.661, p= .000). 5. Score of knowledge level of safety consciousness was mean $71.58{\pm}12.05$ based on Likert 5-point scale with a full mark of 100 points and there was a significance only in current residence of subjects' general characteristics(F or t=3.894, p=.023). 6. Score of knowledge level of first aid was mean $62.73{\pm}13.29$ based on Likert 3-point scale with a full mark of 90 points and there was a significance only in residential type of subjects' general characteristics(F or t=3.058, p= .031). Although college students felt needs of first aid more than middle and high school students, it was found that their actual safety consciousness and knowledge level of first aid were low. Therefore, knowledge and ability should be developed to save human life from all kinds of emergencies and safety accident and first aid subjects should be separated in college curriculum and opportunity for actual education should be given.

• Journal of Technology Innovation
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• v.13 no.2
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• pp.23-43
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• 2005

Industrial clusters are geographical concentrations of interconnected companies, specialised suppliers, service providers, firms in related industries, and associated institutions (for example, universities, standard agencies, and trade associations) that combine to create new products and/or services in specific lines of business. At present, the concept of industrial cluster becomes very popular worldwide, policy makers at national, regional and local levels and business people in both forerunner and latecomer countries are keen to implement the cluster concept as an economic development model. Though understanding of clusters and related promoting policies varies from one place to another, the underlying benefits of clusters from collective learning and knowledge spillovers between participating actors strongly attract the attention of these people. In Thailand, a latecomer country in terms of technological catching up, the cluster concept has been used as a means to rectify weakness and fragmentation of its innovation systems. The present Thai government aspires to apply the concept to promote both high-tech manufacturing clusters, services clusters and community-based clusters at the grass-root level. This paper analyses three very different clusters in terms of technological sophistication and business objectives, i.e., hard disk drive, software and chili paste. It portrays their significant actors, the extent of interaction among them and the evolution of the clusters. Though are very dissimilar, common characteristics attributed to qualified success are found. Main driving forces of the three clusters are cluster intermediaries. Forms of these organizations are different from a government research and technology organization (RTO), an industrial association, to a self-organised community-based organization. However, they perform similar functions of stimulating information and knowledge sharing, and building trust among participating firms/individuals in the clusters. Literature in the cluster studies argues that government policies need to be cluster specific. In this case, the best way to design and implement cluster-specific policies is through working closely with intermediaries and strengthening their institutional especially in linking member firms/individuals to other actors in clusters such as universities, government R&D institutes, and financial institutions.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• Knowledge Management Research
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• v.24 no.3
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• pp.149-172
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• 2023

With the development of information technology, new technologies to be introduced in each industry are continuously increasing. This study aims to verify the influence of ambivalent emotions experienced when encountering new technologies, the coping strategies they induce, and their impact on the decision-making process of technology adoption Specifically, this research investigates the emotions and responses to new technologies in the situational context where service providers must deliver services based on new technology in environments where no such services have been developed previously. Furthermore, it seeks to verify the influence of coping responses on the intention to use services based on new technologies. To this end, this study investigated the ambivalent emotions and coping responses of financial sector workers to new financial services based on metaverse technology. As a result of the analysis ambivalance had a significant effect on all four coping responses (disengagement-oriented coping, denial, indecision and compromise). Among them, denial, which is an inflexible response, and compromise, which is a flexible response, had a significant positive effect on the intention to use, and disengagement-oriented coping and indecision had a significant negative effect on the intention to use. The results of this study confirm the user's metaverse acceptance factor and user-centered influence, and are expected to provide guidelines for the introduction of services to practical workers with academic significance.