• Proceedings of the Korea Contents Association Conference
• /
• 2007.11a
• /
• pp.167-171
• /
• 2007

Application areas of Knowledge Discovery in Database (KDD) have been expanded into many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has recently fully utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not cheap, korean language process not available, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information (KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. Knowledge Matrix main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• The Journal of the Korea Contents Association
• /
• v.20 no.7
• /
• pp.66-85
• /
• 2020

The purpose of this study is to explain and predict trends the AI development process based on AI technology patents (total) and AI reporting frames in major newspapers. To that end, a summary of South Korean and U.S. technology patents filed over the past nine years and the AI (Artificial Intelligence) news text of major domestic newspapers were analyzed. In this study, Topic Modeling and Time Series Return Analysis using Big Data were used, and additional network agenda correlation and regression analysis techniques were used. First, the results of this study were confirmed in the order of artificial intelligence and algorithm 5G (hot AI technology) in the AI technical patent summary, and in the news report, AI industrial application and data analysis market application were confirmed in the order, indicating the trend of reporting on AI's social culture. Second, as a result of the time series regression analysis, the social and cultural use of AI and the start of industrial application were derived from the rising trend topics. The downward trend was centered on system and hardware technology. Third, QAP analysis using correlation and regression relationship showed a high correlation between AI technology patents and news reporting frames. Through this, AI technology patents and news reporting frames have tended to be socially constructed by the determinants of media discourse in AI development.

• Journal of Korea Technology Innovation Society
• /
• v.18 no.1
• /
• pp.98-125
• /
• 2015

This study will show the determinants of research productivity by fields in science and engineering. However, we present the differences between fields by personal attributes, research resources, and research productivities. The data includes 1,383 researchers who participated in the BK21 PLUS program during 2010-2012. The fields are physics, chemistry, biology, mechanics, electricity and electronics and chemical engineering. As for research productivity, 3 indices are used such as the number of papers publicized, patents and combination of papers and patents. As for explanation factors, two kinds of variables are used. The personal factors include sex, age, academic rank, location of affiliation, and country of PhD acquisition, and the resource factors are the number of graduate students, 3 types of research funds such as government fund, industrial fund and overseas fund. This study is unique in several aspects; Dealing with 3 productivity indices, and using massive official data, 6 different fields, and determinants of research productivity. The results are as follows; 1) there is a big difference in determinants by fields. 2) No variables affect the research productivity of all the fields at the same time. 3) In science, the number of determinants are quite low than engineering. 4) The ratio between papers and patents are different by fields. 5) The correlations between paper and patent by fields are different; no relationship in the field of physics and chemistry and positive relationship in the other 4 fields.

• Journal of Distribution Science
• /
• v.13 no.6
• /
• pp.71-78
• /
• 2015

Purpose - This study attempts to analyze whether or not there are characteristics among the top management of companies that promote corporate performance at venture companies. It investigates the characteristics of the human and social capital that are inherent in top management at a venture company and conducts an empirical analysis of hypotheses examining if these characteristics will affect utilization of the governmental R&D support system as well as affect the firm's initial success. Research design, data, and methodology - This study conducted theoretical and empirical research together to accomplish the goal of the study. The pilot study researched human capital and social capital as the independent variables; the governmental R&D support system as the parameter; and, the initial success as the dependent variable. The empirical study carried out research on the model, establishment of hypotheses, and the statistical treatment. A survey was conducted targeting top management of high-tech venture companies in Daedeok Innopolis; 500 questionnaires were distributed; and, 222 were collected. Results - The human and social capital inherent in top management at venture companies in the early stages of their existence become good evaluation data for those who are invested in similar resources. If top management includes strong human and social capital, access to external resources will be easier; these will have a positive influence on the selection of overnmental support systems; and, this proper support will also have a positive influence on the initial success of the venture company. The results revealed the following. First, it was found that when the educational level and functional background, (the top management human capital), are the output function, top management human capital had a significant influence on selection of governmental R&D support funds. Second, it was found that the internal social capital and external social capital, (the top management social capital), had a significant influence on selection of governmental R&D support tasks. Third, it was found that selection of the governmental R&D support tasks at the start of the venture company had a positive influence on the corporate financial performance such as sales, business profits, and the increase in workers; and, had a significant influence on nonfinancial performance such as market share, competitive position, product competitiveness, and the future product development. Conclusions - Selection of the governmental R&D support system is not recognized as part of the direct sales of a venture company in its early stages, but as it can reduce costs for technical development and helps significantly in creating test products and mass production, it has a positive influence on the company's financial performance and nonfinancial performance as a result. Therefore, companies should take great efforts to frequently be selected as a candidate in the governmental R&D support system, as it can help facilitate R&D that requires extensive funds. As a result, companies can expect effects such as job creation and patent applications and they can advance future product sales.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.2
• /
• pp.31-40
• /
• 2017

In this paper, we compared the efficiencies of national R&D investments between NT (Nanotechnology) areas in terms of papers, patents, and commercializations, and found ways to improve the efficiencies of national R&D investments for each NT area. This is in response to huge R&D investments government has made recently in NT areas. Here, we collected data on investments, papers, patents, and commercializations for the R&D projects in NT areas through National Science & Technology Information Service. Based on the data, we analyzed the investment and performances (papers, patents, and commercializations) for each NT area, calculated the efficiency for each NT area, and compared the efficiencies between NT areas. Next, using cluster analysis, we identified several NT areas with similar characteristics in terms of paper efficiency, patent efficiency and commercialization efficiency. Finally, we derived implications for the efficiency enhancement for each grouping. The cluster analysis showed that there could be two groups, one being low in terms of technological outcome (papers and patents) efficiencies and high in terms of commercialization efficiencies, while the other being high in terms of technological outcome (papers and patents) efficiencies and low in terms of commercialization efficiencies. Therefore, the strategy for one group calls for support for technology transfer or technology introduction from other R&D performers and grant of guidance for improving R&D performers' commercialization ability to other R&D performers while the strategy for the other group calls for R&D support for transfer of technology to other R&D performers, activation of technology transfer and support for commercialization of R&D performers.

• Journal of Korean Clinical Nursing Research
• /
• v.19 no.3
• /
• pp.432-442
• /
• 2013

Purpose: The purpose of this study was to describe restraint use in care of patients with psychiatric disorders in an attempt to avoid unnecessary restraint use and provide information for developing standards regarding restraint use as a therapeutic maneuver. Methods: For this descriptive study, discharge records from N National Mental Hospital in the year 2009 were reviewed by trained nurses during Dec. 24, 2010 and Mar. 31, 2011. There were 596 restrains applied on 232 of 1,322 discharges. Data collected include general characteristic of patients, the frequency of restraint use, time since admission when restraint was applied, time of the day when restraint was applied, duration of restraint application, place of occurrence, reasons for restraint use, and degree of damage to the patent. Work experience of nurses who applied restraints, number of workforce at the time of restraint, and season of the year was also identified. Descriptive statistics, Chi-square test, t-test, ANOVA, $Scheff{\grave{e}}$ and Jonckheere-Terpstra were applied using SPSS 14.0 to analyze the data. Results: There were 596 restraint uses among 232 patients. Restraints were applied most frequently on males in their 40s, patients diagnosed with schizophrenia, and patients repeating admissions more than 6 times. Restraints were frequently applied within first week following admission, between 16:00 and 20:00, and the average duration of restraint was 5 hours. There were significant differences according to diagnoses of patients in the season restraint occured, time, place of occurrence, reason for restraint, and duration of restraint. Patients with alcoholism received longer restraint application. Conclusion: In order to avoid unnecessary restraint use in patients with psychiatric disorders, nurses and other health care team members need to acknowledge a group of patients such as patients with schizophrenia and alcoholism who relatively frequently restrained or receiving longer restraint. Reasonable and careful decision need to be made when applying restraint in the care of patients with alcohol problem.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.6
• /
• pp.1161-1170
• /
• 2014

In global competition like today, intellectual property of novel areas such as traditional knowledge, traditional creation, hereditary resource, etc. are perceived as important resources. Therefore making solid competitive power in overall knowledge resources like cultural contents, brand, design etc. in nation is a pressing question. Accordingly in this study, to prepare for intellectual property rights dispute and advantage-sharing problem that would be variously derived from the Nagoya Protocol which will come into force after 2014, this research selected 200 knowledge of middle region in Korea from 2,047 literal and 931 oral knowledge using preconditioning process. The order of priority of top 50 of them was ranked by a quantitative research method, the Delphi survey. Among them, 30 was literal traditional knowledge and 20 was oral traditional knowledge. Result of this research could be used later as basic material for qualitative researches like the focus group interviewing. Furthermore in this paper is meaningful; the selected traditional knowledge can contribute remarkably to traditional biologic knowledge resource in nation which can be acknowledged in international society, announcing validity (hold precedence for patent) later on.

• Journal of Technology Innovation
• /
• v.29 no.4
• /
• pp.1-30
• /
• 2021

Due to the recent development of system semiconductors, technical innovation for the electric devices of the automobile industry is rapidly progressing. In particular, the electric device of automobiles is accelerating technology development competition among automobile parts makers, and the development cycle is also changing rapidly. Due to these changes, the importance of strategic planning for R&D is further strengthened. Due to the paradigm shift in the automobile industry, the Product-Technical Roadmap (P/TRM), one of the R&D strategies, analyzes technology forecasting, technology level evaluation, and technology acquisition method (Make/Collaborate/Buy) at the planning stage. The product-technical roadmap is a tool that identifies customer needs of products and technologies, selects technologies and sets development directions. However, most companies are developing the product-technical roadmap through a qualitative method that mainly relies on the technical papers, patent analysis, and expert Delphi method. In this study, empirical research was conducted through simulations that can supplement and strengthen the product-technical roadmap centered on the automobile industry by fusing Gartner's hype cycle, cumulative moving average-based data preprocessing, and deep learning (LSTM) time series analysis techniques. The empirical study presented in this paper can be used not only in the automobile industry but also in other manufacturing fields in general. In addition, from the corporate point of view, it is considered that it will become a foundation for moving forward as a leading company by providing products to the market in a timely manner through a more accurate product-technical roadmap, breaking away from the roadmap preparation method that has relied on qualitative methods.

• Management & Information Systems Review
• /
• v.38 no.3
• /
• pp.55-80
• /
• 2019

Recently, many companies improving their management performance by building a powerful brand value which is recognized for trademark rights. However, as growing up the size of online commerce market, the infringement of trademark rights is increasing. According to various studies and reports, cases of foreign and domestic companies infringing on their trademark rights are increased. As the manpower and the cost required for the protection of trademark are enormous, small and medium enterprises(SMEs) could not conduct preliminary investigations to protect their trademark rights. Besides, due to the trademark image search service does not exist, many domestic companies have a problem that investigating huge amounts of trademarks manually when conducting preliminary investigations to protect their rights of trademark. Therefore, we develop an intelligent similar trademark search model to reduce the manpower and cost for preliminary investigation. To measure the performance of the model which is developed in this study, test data selected by intellectual property experts was used, and the performance of ResNet V1 101 was the highest. The significance of this study is as follows. The experimental results empirically demonstrate that the image classification algorithm shows high performance not only object recognition but also image retrieval. Since the model that developed in this study was learned through actual trademark image data, it is expected that it can be applied in the real industrial environment.

• The Journal of Society for e-Business Studies
• /
• v.26 no.2
• /
• pp.123-141
• /
• 2021

As the dependence of technology on the economic structure increases, the importance of National Core Technology is increasing. However, due to the nature of the technology itself, it is difficult to determine the scope of the technology to be protected because the scope of the relation is abstract and information disclosure is limited due to the nature of the National Core Technology. To solve this problem, we propose the most appropriate literature type and method of analysis to distinguish important technologies related to National Core Technology. We conducted a pilot test to apply TF-IDF, and LDA topic modeling, two techniques of text mining analysis for big data analysis, to four types of literature (news, papers, reports, patents) collected with National Core Technology keywords in the field of Display industry. As a result, applying LDA theme modeling to patent data are highly relevant to National Core Technology. Important technologies related to the front and rear industries of displays, including OLEDs and microLEDs, were identified, and the results were visualized as networks to clarify the scope of important technologies associated with National Core Technology. Throughout this study, we have clarified the ambiguity of the scope of association of technologies and overcome the limited information disclosure characteristics of national core technologies.