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Many researchers jointly participate in various research topics of national R&D programs, and they achieve accomplishments such as journal papers and patents as the outcome of these programs. The government administration and research administering institutes also do their part in the advancement of national science and technology by strategically distributing R&D programs to researchers, reviewing research outcomes, and setting up investment policies accordingly. Policymakers including government administrations that distribute and manage R&D finance are interested in understanding that the key players are in a given field, how the research clusters are formed, and how the research funding is distributed. Researchers are interested to look at what other researchers are doing and who their potential collaborators are This study proposes a method to provide information wanted by both policymakers and researchers. Based on the proposed method, it builds a knowledge map using the NTIS data to analyze research behavior and statistics of various research topics.

Emerging technology drives technological development and innovation in diverse fields of technology. Emerging technology forecasting can predict the possible areas of emerging technology. However, it is difficult to forecast the emerging technology because most technology forecasting tasks depend on the subjective experience of experts. Patent analysis is an objective method to recognize the trends in technological development. Many patent analysis methods have been researched; these methods apply text mining techniques to analyze the text data of patent documents such as the title and abstract. This approach has some limitations, namely the computing cost and information loss associated with the preprocessing step of text mining. Therefore, we propose a new patent information analysis to overcome these problems. Using the International Patent Classification codes from the patent documents of a target technology, we construct an emerging technology forecasting model. This research combines statistical inference and neural networks to construct our model for new patent information analysis. We perform a case study to verify how our research can be practically applied, using nanotechnology as the target technology. Therefore, we contribute this research to R&D planning.

A data scientist is a relatively new job title and is not yet fully defined or understood. Little research has been conducted on data scientists and there is still incongruity among its practitioners. Yet, the job market for data scientists is already active with high demand. Many companies have created their own definition of a data scientist based on their own needs. The purpose of this research is to explore the definition of a data scientist by examining how it is accepted in these industries and businesses. A content analysis of 1,240 job ads from various companies recruiting data scientists was conducted to identify what types of knowledge and skills were generally demanded. As a result, we found that data scientists were expected to be highly experienced professionals with advanced degrees. The main requisite areas of profession were statistics, modeling, machine learning, and analysis.

In this paper, we propose the clustering-based ensemble management system which extracts new data patterns from the input streaming data by using clustering and generates new classification models only when a certain amount of data has been collected in a cluster. The clustering-based ensemble management system can reduce the number of the data labeling and keep the accuracy of the existing ensemble. The clustering-based ensemble management system collects similar patterned data from the input streaming data for building a cluster. The clustering-based ensemble management system performs the data labeling for the each cluster only when a certain amount of data has been collected in the cluster. The data labeling by experts goes on to generate the new classification model to be added to the ensemble. The clustering-based ensemble management system applies the K-NN technique to classification model units in order to keep the accuracy of the existing system while it uses a small amount of data. The efficiency of the clustering-based ensemble management system proposed in this paper is shown by the simulated results for benchmarks comparing with the existing ensemble techniques.

This study is an analysis of the research trends of the Korean Journal of Educational Research, the leading journal in the study of Korean education. In this paper, the semantic network analysis method that applies to social network analysis was used to measure the frequency of certain types of research themes in order to examine their connection centrality and network diagram. This paper examined 355 theses published from 2006 to 2015. The results of the analysis revealed that the keyword "academic achievement" appeared most frequently (34 times), followed by “self-efficacy,” (24) “learner,” (17) “curriculum,” (16) “education,” (14) “teaching and learning,” (13) and “multicultural education.” (13) In the network diagram, the keywords of “learner,” “sense of efficacy,” “private education,” “academic achievement,” “assessment,” and “curriculum” demonstrated high centrality. Among these keywords, a network was formed centering around words such as “learner,” “assessment,” “academic achievement,” “sense of efficacy,” and “curriculum.” In other words, this indicates that these keywords are often associated with the research process. In this study, moreover, a network text cluster map with a wide variety was formed. This demonstrated that the Korean Journal of Educational Research covers a range of study contents of subcategories within the field of education. This paper examines the core themes of education, their connectivity and connection centrality, and a map of network clusters.

Banks recorded minus returns due to the subprime mortgage crisis in 2008 and regulations on financial instruments. To overcome this, the financial industry has replaced its system, which originally has been done by human, to computer system while joining hands with the IT industry. As time goes by, consumers tend to go online instead of visiting banks as the costs of financial services have been reduced and their speed gets fast. The purpose of this study is to find out what forms psychological resistance regarding internet banks and empirically verify what actually influences the intent to use internet banks. Thus, this study tries to reveal factors that form psychological resistance inhibiting the proliferation of internet banks through study models comprised of the variables suggested in the Innovation Resistance Model by Ram.

With the remarkable development of digital technology, wireless communication, and smartphone device, there have been made various transformations in a wide range of technology. In addition, various service platforms appear as well, which gradually lead to the interest in digital content and portal sites as an open cooperative platform. However, practical use of digital contents has not well produced profits by using its strength properly so far. Thus, I investigated the impact of usage way of open cooperative platform as an example of successful case. For this purpose, I established Webtoon characteristic and the open cooperative factor as independent variables. I set and analyzed the participation of cooperative creation activity and user’s satisfaction as parameter to show the greater impact of elements by establishing user’ intention as an independent variable by applying various digital contents.

This paper defines the various resources for developing software product line (SPL) and presents the resource versioning scheme for evolutionary SPL based system development and maintenance. For the resource versioning, we suggest the resource versioning identifiers and how to maintain the resources with the identifiers to keep consistency between software artifacts in the SPL and its derived products. In addition, the resource identifiers are simulated in the diverse SPL and product evolution scenarios. The approach has been applied to building the SPL based Home Service Robot system and its maintenance.

The growth of South Korea’s tourism industry, in turn, has led to a steady growth in the number of international visitors to South Korea (hereinafter referred to as “Korea”). When visiting Korea, foreign visitors are likely to turn to smartphones as the most convenient tool for getting the information they need. A survey by Korea Tourism Organization found that tourists usually search for the information they need on their smartphones. This study was, however, based on the assumption that it is an application (hereinafter “app”) that can provide the most extensive tourist information about Korea. Thus, the study involves analyzing currently available services while centering on the “Visit Korea” app distributed by Korea Tourism Organization, and comparing it with other apps to come up with suggestions for improvement. Integrating Bluetooth 4.0-enabled beacons with mobile apps will provide travelers with useful services, convenience, and a variety of benefits. It is also an easier and more assuring method for administrators when they identify users’ data. As for the problems associated with beacons, incremental improvements are also being made. Combining the “Visit Korea” app with beacon technology will hopefully contribute to the further growth of the Korean tourism industry.

Given that usability is one of the most important aspects of software quality, several methods have been developed in order to establish techniques capable of evaluating this attribute from early phases of the software development process. However, the choice of the most appropriate method for a particular scenario is still a difficult decision, due to the existence of a vast number of approaches that are described in the literature for this purpose. Therefore, a systematic mapping review was conducted in order to identify the most commonly used usability evaluation techniques in software developments. A total of 1169 studies were identified, of which only 215 studies were selected for this review. According to the analysis, most cases studies establish the use of usability questionnaires as assessment tool. In addition, health informatics and Web applications are the software domain and type of application that are frequently reported in these evaluations. This work has allowed to reach promising results in this area. It is intended to be a guide for specialists to support the choice of the most suitable method for a particular scenario.