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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.

This study aims to increase our understanding about information seeking behavior via a field study, mediating user-and system-centered approach. In the user-centered view, we investigate if the information type and value offering channels vary according to information seeking purpose. In addition, we examine which channel the users select for the purpose of information use under the system-centered approach, and what differences occur depending on variables such as researchers’ affiliation and research capabilities. We try to identify characteristics of users in Korea and how they are differentiated with others. A survey was made online over 4 weeks and 921 usable responses were left and used. We suggested five hypotheses in research framework and examine these statistically. In conclusion, we derived some insights for national S&T information service strategies from three perspectives - information service, information brokerage and negotiator perspective against worldwide publishing companies

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.

Software has been a significant part of modern society for a long time. In particular, this paper is concerned with various software development process models. Software process model is a description of the sequence of activities carried out in a software engineering project, and the relative order of these activities. It represents some of the development models namely, waterfall, v-shaped, incremental, RAD, iterative spiral and agile model. Therefore, the main objective of this paper is to represent different models of software development and different aspects of each model to help the developers to select specific model at specific situation depending on customer demand.

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 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.

This study focused on most existing researches related to eco-friendly agricultural goods are subject to offline stores, but the area is to be widened to the internet shopping mall environment in this study. Also, the influence of e-servicescape and consumption propensity of customers using eco-friendly agricultural specialized internet shopping malls on emotional response and behavior intention of customers is to investigated. Based on this, the influence of consumption emotion, which was selected as a parameter, on mind share required to improve competitiveness of eco-friendly agricultural specialized internet shopping malls is to be revealed. As result of analysis in this study, it could be known that e-servicescape and consumption propensity both have positive influence on continuous use intention. Also, it was found that consumption emotion also has positive influence on continuous use intention. This means that consumers can increase continuous use intention through e-servicescape and consumption propensity of eco-friendly agricultural goods are subject to offline stores and can increase continuous use intention through the consumption emotion that is felt in consumer experience. Especially, regarding on which factor between e-servicescape and consumption propensity has more influence, only e-servicescape and consumption propensity showed influence on continuous use intention as result of inserting consumption propensity, e-servicescape, consumption propensity, and consumption emotion. As result of analyzing mediation effect, it could be known that consumption emotion is a more significant factor than consumption propensity from the result that consumption emotion partially mediates between consumption propensity and continuous use intention. However, mediation effect of consumption emotion between e-servicescape and continuous use intention was shown in which it could be known that e-servicescape was the most important factor. Therefore, it is considered that the eco-environment agricultural product market can create situations more developed than specialized internet shopping malls if eco-environment agricultural product specialized internet shopping malls are constructed and operated based on these research results in which it can be said in this part that this research provides theoretical∙ practical implications.

The Life cycle for the development of traditional commercial software is well established and discussed in various texts and research papers in detail. But in case of Open Source Software (OSS) life cycle for the development is not being discussed in much detail as there is no standardized life cycle approach exists for Open Source Software (OSS) development. Different researchers and developers have proposed various life cycles for the development of OSS with respect to their own development experience, need, or application. The main focus of this paper is on reviewing and then comparing the existing Open Source Software Life Cycle (OSSLC) presented and proposed by the various researchers and practitioners. It will give a precise view that in actual what are the various development approaches are used in case of OSS and how development of open source software starts and proceeds.