• Journal of Korean Institute of Industrial Engineers
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• v.42 no.3
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• pp.231-240
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• 2016

As the limitation of the existing convergence is pointed out, technology-humanities convergence which highlights the enhancement of the quality of life of humans, is focused as a solution to facilitate sustainable technological innovation. Technology-humanities convergence has already occurred in various industries, of which a considerable number of successful cases can be noted. However, few efforts have been made to investigate technologyhumanities convergence as an independent academic field. Therefore, this paper aimed to identify the status of technology-humanities convergence. To do this, first, a definition of technology-humanities convergence was proposed. Second, based on Maslow's theory, the types of human needs and related key words were extracted. Third, patents related to human needs were collected from the United States Patent and Trademark Office (2000~2014). Fourth and last, the status of technology-humanities convergence was analyzed in terms of "convergence trends" and "convergence areas." This research is expected to promote more creative and human-centered performances of innovation as well as to support decision-making when the innovation strategy-as attempted by the quantitative analysis of technology-humanities convergence in the perspective of sustainable competitiveness-is established.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.101-107
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• 2018

Recently, Korea's defense industry has advanced highly, and defense R&D budget is gradually increasing in defense budget. However, without objective analysis of defense industry technology, effective defense R&D activities are limited and defense budgets can be used inefficiently. Therefore, in addition to analyzing the defense industry technology quantitatively reflecting the opinions of the experts, this paper aims to analyze the defense industry technology objectively by quantitative methods, and to make efficient use of the defense budget. In addition, we propose a patent analysis method to grasp the characteristics of the defense industry technology and the vacant technology objectively and systematically by applying the big data analysis method, which is one of the keywords of the 4th industrial revolution, to the defense industry technology. The proposed method is applied to the technology of the firepower industry among several defense industrial technologies and the case analysis is conducted. In the process, the patents of 10 domestic companies related to firepower were collected through the Kipris in the defense industry companies' classification of the Korea Defense Industry Association(KDIA), and the data matrix was preprocessed to utilize IPC codes among them. And then, we Implemented association rule mining which can grasp the relation between each item in data mining technique using R program. The results of this study are suggested through interpretation of support, confidence lift index which were resulted from suggested approach. Therefore, this paper suggests that it can help the efficient use of massive national defense budget and enhance the competitiveness of defense industry technology.

• Smart Media Journal
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• v.11 no.10
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• pp.46-53
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• 2022

Today, due to the 4th industrial revolution and extensive R&D funding, domestic companies have begun to possess world-class industrial technologies and have grown into important assets. The national government has designated it as a "national core technology" in order to protect companies' critical industrial technologies. Particularly, technology leaks in the shipbuilding, display, and semiconductor industries can result in a significant loss of competitiveness not only at the company level but also at the national level. Every year, there are more insider leaks, ransomware attacks, and attempts to steal industrial technology through industrial spy. The stolen industrial technology is then traded covertly on the dark web. In this paper, we propose a system for detecting industrial technology leaks in the dark web environment. The proposed model first builds a database through dark web crawling using information collected from the OSINT environment. Afterwards, keywords for industrial technology leakage are extracted using the KeyBERT model, and signs of industrial technology leakage in the dark web environment are proposed as quantitative figures. Finally, based on the identified industrial technology leakage sites in the dark web environment, the possibility of secondary leakage is detected through the PageRank algorithm. The proposed method accepted for the collection of 27,317 unique dark web domains and the extraction of 15,028 nuclear energy-related keywords from 100 nuclear power patents. 12 dark web sites identified as a result of detecting secondary leaks based on the highest nuclear leak dark web sites.

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

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.35-45
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• 2012

Researchers and scientists spend huge amount of time in analyzing the previous studies and their results. In order to timely take the advantageous position, they usually analyze various resources such as paper, patents, and Web documents on recent research issues to preoccupy newly emerging technologies. However, it is difficult to select invest-worthy research fields out of huge corpus by using the traditional information search based on keywords and bibliographic information. In this paper, we propose a method for efficient creation, storage, and utilization of semantically relevant information among technologies, products and research agents extracted from 'big data' by using text mining. In order to implement the proposed method, we designed an ontology that creates technological knowledge for semantic web environment based on the relationships extracted by text mining techniques. The ontology was utilized for InSciTe Adaptive, a R&D trends analysis and forecast service which supports the search for the relevant technological knowledge.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.490-498
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• 2010

In the web or not, all academic information have the creator which produces that information. The creator can be individual, organization, institution, or country. Most information consist of the title, author and content. The article among academic information is described by title, author, keywords, abstract, publisher, ISSN(International Standard Serial Number) and etc., and the patent information is consisted some metadata such as invention title, applicant, inventors, agents, application number, claim items etc. Most web-based academic information services provide search functions to user by processing and handling these metadata, and the search function using the author field is important. In this paper, we propose an effective indexing management for person name search, and search techniques using boosting factor and near operation based on phrase search to improve precision rate of search result. And we describe person name retrieval result with another expression name, co-authors and persons in same research field. The approach presented in this paper provides accurate data and additional search results to user efficiently.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.2
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• pp.317-324
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• 2016

This paper is to provide information for quantitative evaluation of suspension bridge engineering and construction technology, technology development, and long-span bridge R&D agenda. Technology classification structure and key words are established and survey to identify technology level is performed. Then, competitiveness of patents and journal articles is evaluated for Korea, USA, Japan, Germany, France, and England. As a result, USA and Japan are generally competitive countries for all technology categories based on patents and journal articles. Korea is grouped in upper-middle class for overall technology level of suspension bridge. However, there are some variances among the level of technologies. This research results could be utilized as reference to establish future long-span bridge R&D. Also, it can be a standardized methodology to compare technology levels among countries.

• Journal of the Korean Regional Science Association
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• v.39 no.3
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• pp.35-48
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• 2023

This study analyzed the inflow factors of Yangjae Citizen's Forest Park using social big data generated online. To this end, the applicability of the emotional information analysis method is to be confirmed as a method of analyzing the perception of the city park and confirming the difference in the characteristics and use of the park. The analysis is based on big data, and as the core of the study is keyword network analysis, the methodology of the 'emotional information analysis method' patented by the author was applied. As a result of the analysis, among the influx factors of Yangjae Citizens' Forest recognized by citizens, the most positive emotional factor was derived as a factor related to 'park contents', and the negative emotional factor was derived as a factor related to 'park management'. These research results suggest that more in-depth program development and operation are needed to discover 'park contents' when implementing urban park revitalization support projects in the future

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.555-563
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• 2016

Science and technology contents (research papers, patents, reports) are the most common reference material for researchers involved in research and development in the fields of science and technology. Based on various search elements (title, abstract, keyword, year of publication, name of journal, name of author, publisher, etc.), many services are available for users to search science and technology contents and bibliographic information owned by libraries. Authority data on organization name can be useful as an element for author identification and as an element to search for results produced by specific organizations. However, organization name is not taken into account by current search services for domestic academic information and bibliographic records. This study analyzes organization name data contained in the metadata of science and technology contents, which are the basis of the establishment of authority data, and proposes a method and system based on string containment and exact string matching.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.575-584
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• 2013

Data types used for big-data analysis are very widely, such as news, blog, SNS, papers, patents, sensed data, and etc. Particularly, the utilization of web documents offering reliable data in real time is increasing gradually. And web crawlers that collect web documents automatically have grown in importance because big-data is being used in many different fields and web data are growing exponentially every year. However, existing web crawlers can't collect whole web documents in a web site because existing web crawlers collect web documents with only URLs included in web documents collected in some web sites. Also, existing web crawlers can collect web documents collected by other web crawlers already because information about web documents collected in each web crawler isn't efficiently managed between web crawlers. Therefore, this paper proposed a distributed web crawler. To resolve the problems of existing web crawler, the proposed web crawler collects web documents by RSS of each web site and Google search API. And the web crawler provides fast crawling performance by a client-server model based on RMI and NIO that minimize network traffic. Furthermore, the web crawler extracts core content from a web document by a keyword similarity comparison on tags included in a web documents. Finally, to verify the superiority of our web crawler, we compare our web crawler with existing web crawlers in various experiments.