• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.1-20
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• 2021

As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.17-39
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• 2024

The purpose of this study was to analyze the effect of the government's R&D support and the use of stock options by venture companies on the innovation of venture companies, that is, innovation capabilities and innovation performance. An empirical analysis was conducted using the partial least squares structural equation modeling (PLS-SEM) method using the data from the detailed survey of venture companies conducted on domestic venture confirmation companies. As a result of the analysis, it was found that the benefit of government R&D support had a positive (+) effect on strengthening the innovation capabilities of venture companies, and R&D support also had a positive (+) effect on the innovation performance of venture companies. Next, it was found that the use of stock options by venture companies had a positive (+) effect on the reinforcement of the innovation capabilities of companies and a positive (+) effect on the innovation performance of venture companies. In addition, it was found that the innovation capabilities of venture companies significantly mediate between the government's R&D support and the use of stock options by venture companies and the innovation performance of companies. These analysis results show that the government's R&D support and the use of stock option systems can play a meaningful role in the innovation of venture companies, and also show that the innovation capabilities of venture companies have an important meaning in the process of innovation. Therefore, it is necessary to continue the stance of R&D support for ventures and at the same time to introduce multi-faceted policy measures to support corporate capacity building, and legal and institutional maintenance and policy support to revitalize the stock option system need to be continuously provided.

• Korean Journal of Social Welfare Studies
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• v.41 no.1
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• pp.175-201
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• 2010

The purpose of this study was to examine the mechanism through which youth school-based mentoring program impacts mentees' psychological and school-related outcomes such as self-esteem, self-efficacy, and attitudes toward school. The hypothetical model was assumed that mentors could improve their mentees' developmental outcomes through positive relationships with mentors as good role models and enhancement of help-seeking orientation. To investigate the mediating effect of process-related outcomes, structural equation modeling was used. The 97 adolescents were recruited through referral and random selection from middle schools in Seoul. The result showed that the effects of program participation were mediated by proximal changes in connectedness to role models and development of help-seeking orientation that, in turn, led to facilitate more positive attitudes toward school and academic activity, and improve psychological outcomes. Practice and policy implications as well as further research topics were discussed to aid the search for highly effective mentoring programs.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.455-458
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• 2013

The conventional design of the information system architecture based on the personal experience of information systems has been acted as a limit in progress utilizing appropriate resource allocation and performance improvements. Architecture design depending on personal experience makes differences in variance of a designer's experience, intellectual level in related tasks and surroundings, and architecture quality according to individual's propensity. After all these problems cause a waste of expensive hardware resources. At working place, post-monitoring tools are diversely developed and are running to find the bottleneck and the process problems in the information operation. However, there are no simulation tools or models that are used for expecting and counteracting the problems at early period of designing architecture. To solve these problems we will first develop a simulation model for designing information system architecture in a pilot form, and will verify validity. If an error rate is found in the permissible range, then it can be said that the simulation reflects the characteristic of information system architecture. After the model is developed in a level that can be used in various ways, more accurate performance computation will be able to do, getting out of the old way relying on calculations, and prevent the existence of idle resources and expense waste that comes from the wrong design of architecture.

• Korean Journal of Construction Engineering and Management
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• v.17 no.5
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• pp.78-88
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• 2016

Recently BIM technology has been expanded for using in construction project. However its spread has been delayed than the initial expectations, due to the high-cost of BIM infrastructure development, the lack of regulations, the lack of process and so forth. In design phase, especially, collaboration based on BIM system has being a key factor for successful next generation building project. Through the analysis of current research trend about IT technologies, virtualization and BIM service, data exchange such as drawing, 3D model, object data, properties using cloud computing and virtual server system is defined as a most successful solution. In various industrial fields, cloud computing technology is utilized as a promising solution which can reduce time and cost of hardware infrastructure. Among the cloud computing technology, VDI is receiving a great deal of attention from it market as an essential part cloud computing. VDI enables to host multiple individual virtual machines by using hypervisor. It has an advantage to easy main device management. Therefore, this study implements a step-by-step user's DaaS by analyzing the desktop resource data of the workers from Pre-design phase to Schematic design, Design develop and Construction design phase. It also develops BIM environment based on test of BIM modeler and designers in architectural design firm. The goal of the study is to enable the cloud computing BIM server. It provides cost saving, high-performance quality of working environment and cooperation's convenience and high security when doing BIM work in small and medium sized architectural design firm.

• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.113-132
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• 2018

Mokpo port marked the $131^{st}$ anniversary of its opening in 2018. while the Mokpo has taken the new port development initiatives, it is limited by inefficient port functioning due to the lack of maritime port policy and government investment. Hence, port logistics has not been activated. Additionally, studies on Mokpo port have not been conducted, and knowledge available on the port is declarative in nature. On the other hand, research on port competitiveness focuses on how to analyze the factors that determine port competitiveness. Therefore, this study was intended to expand the existing research on Mokpo port and conduct an analysis of non-competitiveness factors and suggested improvements by considering the operational aspect of Mokpo port. In this regard the importance of non-competitiveness factors was assessed through an analytic hierarchy process(AHP) analysis and the influence of the non-competitiveness factors was analyzed through an fuzzy structural modeling(FSM) analysis. The result of the AHP analysis show ed the important non-competitiveness factors included the deactivation of industrial complexes around Mokpo port, the number of liner route, the cost of the pilot and tug. Accor ding to the FSM analysis, the top level included the non-competitive factors at Mokpo port; the intermediate level included the number of liner routes, cost of pilot and tug, enrance and clearance fee, costs of inland transportation, fee for port facilities, and loading and unloading costs; and the bottom level comprised the most non-competitive factors including the deactivation of industrial complexes around Mokpo port, hinterland connectivity, access to international port, incentives, and cost of transportation and storage. Based on the results of analysis, improvements were suggested for non-competitive factors of Mokpo.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.13-24
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• 2012

CCGIS (Climate Change Adaptation Toolkit based on GIS) was developed to use as a tool for the climate change assessment and any relevant tasks involving climate change adaptation policy over Korean peninsula. The main objective of CCGIS is to facilitate an efficient and relevant information for the estimation of climate change vulnerability index by providing key information in the climate change adaptation process. In particular, the atmospheric modeling system implemented in CCGIS, which is composed of climate and meteorological numerical model and the atmospheric environmental models, were used as a tool to generate the climate and environmental IPCC SRES (A2, B1, A1B, A1T, A1FI, and A1 scenarios) climate data for the year of 2000, 2020, 2050, and 2100. This article introduces the components of CCGIS and describes its application to the Korean peninsula. Some examples of the CCGIS and its use for both climate change adaptation and estimation of vulnerability index applied to Korean provinces are presented and discussed here.

• The Korean Journal of Archival Studies
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• no.46
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• pp.5-44
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• 2015

This article purposes to define archival justice and suggest democratic modeling of the archive on the Truth and Reconciliation Committee (TRC), which is focused on victims of state violence. These purposes come from critical mind that the absence of framework of the records management for collective memory would cause incorporation of TRC archives into mainstream archives systems in which voices of victims have been marginalized. This article intends to expand theoretical prospects of documentation of past affairs through applying humanistic and theoretical frameworks differently from institutional and policy approaches on restoration of collective memory. In order to do this, this article first considers archival justice as archives building in which state violence' victims are pivotal and then extracts theoretical frameworks for building the archives based on archival justice from recent discourses of post-colonial archives and community archives. As the next step, it criticizes current conditions of TRC archives in Korea on the basis of extracted theoretical frames and finally suggests realistic models in which each theoretical frame could be applied effectively into TRC archives that is focused on victims.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.125-148
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• 2018

Recently, as the demand for big data analysis increases, cases of analyzing unstructured data and using the results are also increasing. Among the various types of unstructured data, text is used as a means of communicating information in almost all fields. In addition, many analysts are interested in the amount of data is very large and relatively easy to collect compared to other unstructured and structured data. Among the various text analysis applications, document classification which classifies documents into predetermined categories, topic modeling which extracts major topics from a large number of documents, sentimental analysis or opinion mining that identifies emotions or opinions contained in texts, and Text Summarization which summarize the main contents from one document or several documents have been actively studied. Especially, the text summarization technique is actively applied in the business through the news summary service, the privacy policy summary service, ect. In addition, much research has been done in academia in accordance with the extraction approach which provides the main elements of the document selectively and the abstraction approach which extracts the elements of the document and composes new sentences by combining them. However, the technique of evaluating the quality of automatically summarized documents has not made much progress compared to the technique of automatic text summarization. Most of existing studies dealing with the quality evaluation of summarization were carried out manual summarization of document, using them as reference documents, and measuring the similarity between the automatic summary and reference document. Specifically, automatic summarization is performed through various techniques from full text, and comparison with reference document, which is an ideal summary document, is performed for measuring the quality of automatic summarization. Reference documents are provided in two major ways, the most common way is manual summarization, in which a person creates an ideal summary by hand. Since this method requires human intervention in the process of preparing the summary, it takes a lot of time and cost to write the summary, and there is a limitation that the evaluation result may be different depending on the subject of the summarizer. Therefore, in order to overcome these limitations, attempts have been made to measure the quality of summary documents without human intervention. On the other hand, as a representative attempt to overcome these limitations, a method has been recently devised to reduce the size of the full text and to measure the similarity of the reduced full text and the automatic summary. In this method, the more frequent term in the full text appears in the summary, the better the quality of the summary. However, since summarization essentially means minimizing a lot of content while minimizing content omissions, it is unreasonable to say that a "good summary" based on only frequency always means a "good summary" in its essential meaning. In order to overcome the limitations of this previous study of summarization evaluation, this study proposes an automatic quality evaluation for text summarization method based on the essential meaning of summarization. Specifically, the concept of succinctness is defined as an element indicating how few duplicated contents among the sentences of the summary, and completeness is defined as an element that indicating how few of the contents are not included in the summary. In this paper, we propose a method for automatic quality evaluation of text summarization based on the concepts of succinctness and completeness. In order to evaluate the practical applicability of the proposed methodology, 29,671 sentences were extracted from TripAdvisor 's hotel reviews, summarized the reviews by each hotel and presented the results of the experiments conducted on evaluation of the quality of summaries in accordance to the proposed methodology. It also provides a way to integrate the completeness and succinctness in the trade-off relationship into the F-Score, and propose a method to perform the optimal summarization by changing the threshold of the sentence similarity.