• Journal of Korea Technology Innovation Society
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• v.20 no.3
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• pp.576-606
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• 2017

It is more salient in the high-tech industry to cooperate even among competitors in order to promptly respond to the changes in product architecture. In this sense, 'co-opetition,' which is the combination word between 'cooperation' and 'competition,' is the new business term in the strategic management and represents the two concepts "simultaneously co-exist." From this view, this study set up the research purposes as follows: 1) investigating the corporate managerial and technological behavioral characteristics in the co-opetition of the global display industry. 2) verifying the emerging factors during the co-opetition behavior hereafter. 3) suggesting the strategic direction focusing on the co-opetition behavioral characteristics. To this end, this study used co-word network analysis to understand the structure in context level of the co-opetition. In order to understand topics on each network, we clustered the keywords by community detection algorithm based on modularity and labeled the cluster name. The results show that there were increasing patterns of competition rather than cooperation. Especially, the litigations for mutual control against Korean firms much more severely occurred and increased as time passed by. Investigating these network structure in technological evolution perspective, there were already active cooperation and competition among firms in the early 2000s surrounding the issues of OLED-related technology developments. From the middle of the 2000s, firm behaviors have focused on the acceleration of the existing technologies and the development of futuristic display. In other words, there has been competition to take leadership of the innovation in the level of final products such as the TV and smartphone by applying the display panel products. This study will provide not only better understanding on the context of the display industry, but also the analytical framework for the direction of the predictable innovation through analyzing the managerial and technological factors. Also, the methods can support CTOs and practitioners in the technology planning who should consider those factors in the process of decision making related to the strategic technology management and product development.

• The Journal of the Korea Contents Association
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• v.16 no.11
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• pp.253-263
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• 2016

We analyzed the social issue 'image of the elderly' using Big Data and Social Network Analysis. First, we analyzed the words extracted by the text mining technique by inputting the keyword 'elderly'. As a result of analysis, the image of the elderly viewed through media such as cafes, blogs, etc. Representing the trend of the public was using the word 'Senior' the most. The image of the elderly is expressed using the word having the highest frequency in the top 10, "The elderly are 'Senior' people who are respected by society, they are organized to earn money, to earn their qualifications, to health, and to 'Seniors' who desire to work healthy up to 100 years old". The purpose of this study is to differentiate from the existing analysis method by analyzing the macro-level image of the elderly including the social discourse by collecting vast amount of data and analyzing it with the social networking technique. When the image of the elderly that the public perceives is positively expressed as 'Senior', it can be said that the direction of the current elderly policy is evaluated as a desirable direction. On the other hand, it was able to feel the 'desire' of the public who wanted to be evaluated. Therefore, the policy direction of the elderly to be applied in the future should be the policy that enables the elderly to be perceived as 'Necessary existence' in society by taking on social roles. In addition, we proposed to implement the policy of the elderly that reflects priorities such as job creation, welfare, and alienation that can activity and maintain health.

• The KIPS Transactions:PartD
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• v.8D no.1
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• pp.71-80
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• 2001

Object-Oriented (OO) methodology to use the concept like encapsulation, inheritance, polymorphism, and message passing demands metrics that are different from structured methodology. There are many studies for OO software metrics such as program complexity or design metrics. But the metrics for the analysis class need to decrease the complexity in the analysis phase so that greatly reduce the effort and the cost of system development. In this paper, we propose new metrics to measure the complexity of analysis classes which draw out in the analysis phase based on Unified Process. By the collaboration complexity, is denoted by CC, we mean the maximum number of the collaborations can be achieved with each of the collaborator and detennine the potential complexity. And the interface complexity, is denoted by IC, shows the difficulty related to understand the interface of collaborators each other. We prove mathematically that the suggested metrics satisfy OO characteristics such as class size and inheritance. And we verify it theoretically for Weyuker' s nine properties. Moreover, we show the computation results for analysis classes of the system which automatically respond to questions of the it's user using the text mining technique. As we compared CC and IC to CBO and WMC, the complexity can be represented by CC and IC more than CBO and WMC. We expect to develop the cost-effective OO software by reviewing the complexity of analysis classes in the first stage of SDLC (Software Development Life Cycle).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.670-681
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• 2016

Recently, based on Internet and mobile environments, the Fintech industry that fuses finance and IT together has been rapidly growing and Fintech services armed with simplicity and convenience have been leading the conversion of all financial services into online and mobile services. However, despite the rapid growth of the Fintech industry, few studies have classified Fintech technologies into detailed technologies, analyzed the technology development trends of major market countries, and supported technology planning. In this respect, using Fintech technological data in the form of unstructured data, the present study extracts and defines detailed Fintech technologies through the topic modeling technique. Thereafter, hot and cold topics of the derived detailed Fintech technologies are identified to determine the trend of Fintech technologies. In addition, the trends of technology development in the USA, South Korea, and China, which are major market countries for major Fintech industrial technologies, are analyzed. Finally, through the analyses of networks between detailed Fintech technologies, linkages between the technologies are examined. The trends of Fintech industrial technologies identified in the present study are expected to be effectively utilized for the establishment of policies in the area of the Fintech industry and Fintech related enterprises' establishment of technology strategies.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.65-87
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• 2017

We propose a method to analyze the user reviews and ratings of the products in the online shopping mall and automatically extracts the features of the products to determine the characteristics of a product. By judging whether a rating is given by a specific feature of a product, our method distributes the score to each feature. Conventional methods force users to wastes time reading overflowing number of reviews and ratings to decide whether to buy the product or not. Moreover, it is difficult to grasp the merits and demerits of the product, because of the way reviews and ratings are provided. It is structured in a way that it is impossible to decide which rating is given to the which characteristics of the product. Therefore, in this paper, to resolve this problem, we propose a method to automatically extract the feature of the product from the user review and distribute the score to appropriate characteristics of the product by calculating the rating of each feature from the overall rating. proposed method collects product reviews and ratings, conducts morphological analysis, and extracts features and emotional words of the products. In addition, a method for determining the polarity of a sentence in which the feature appears is given a weight value for each feature. results of the experiment and the questionnaires comparing the existing methods show the usefulness of the proposed method. We also validates the results by comparing the analysis conducted by the product review experts.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.525-535
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• 2017

The purpose of this study aims to examine consumer perception and current status of water park. The Naver and Daum were used for data collection channels and the keyword 'water park' was used for data retrieval. The data analysis period was limited to the study period from January 1, 2015 to December 31, 2016 for a total of two years. First, as a result of the frequency analysis, hidden cameras, Lotte water park, arrests, suspects, gimhae were in top 5 in 2015, Lotte water park, swimming, summer, opening, admission ticket were in top 5 in 2016. Second, as a result of the connection degree central analysis, hidden camera, arrest, suspect, female, shower room were in top 5 in 2015, swimming, Lotte water park, summer and One Mount, admission ticket were in top 5 in 2016. Third, as a result of the N-GRAM network graph, the water park/hidden camera, the hidden camera/hidden camera, the suspect/arrest, the Gimhae/Lotte water park, water park/suspect were in top 5 in 2015, and One Mount/water park, Gimhae/Lotte water park, water park/admission ticket, water park/water park, water park/opening were in top 5 in 2016. Fourth, as a result of the CONCOR analysis, three groups in 2015 and two groups in 2016 were formed.

• Spatial Information Research
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• v.23 no.3
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• pp.35-44
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• 2015

Recently, the government aims to discover and provide services to citizens on the development strategy for activating the U-City. So, this study aims to offer a service discovery direction by analyzing the service issues and trends. The target is newspaper article about U-City Service from 2009 to 2014. Prepared 723 newspaper article for analysis. Next step is frequency analysis of keyword and used that result for Network analysis and measure of information. Network analysis can show result through "Degree Centrality", "Betweenness Centrality" and "Closeness Centrality". As a result, "Information", "IT", "Environment", "Technology", "Center" is higher than another. These 5 keywords are important factors for driving the U-City the past six years. Information measurement results, Already U-City were put an emphasis on building the infrastructure and able to identify a trend that provided the center of the public service. Those Service field are "Tour(2009)", "Crime prevention and Disaster Prevention(2010)", "Facility Management(2011)", "administration(2012)" and "Facility Management(2013, 2014)". Result of this study found implications what on citizen participation. So, services field on the existing infrastructure should be discovered and provided. Finally, this study can expected to be a reference in the local government planning for U-City.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.33-41
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• 2018

Recently, Internet technology has developed, various programs are being created and therefore various codes are being made through many authors. On this aspect, some author deceive a program or code written by other particular author as they make it themselves and use other writers' code indiscriminately, or not indicating the exact code which has been used. Due to this makes it more and more difficult to protect the code. In this paper, we propose author identification framework using Authorship Analysis theory and Natural Language Processing(NLP) based on Convolutional Neural Network(CNN). We apply Authorship Analysis theory to extract features for author identification in the source code, and combine them with the features being used text mining to perform author identification using machine learning. In addition, applying CNN based natural language processing method to source code for code author classification. Therefore, we propose a framework for the identification of authors using the Authorship Analysis theory and the CNN. In order to identify the author, we need special features for identifying the authors only, and the NLP method based on the CNN is able to apply language with a special system such as source code and identify the author. identification accuracy based on Authorship Analysis theory is 95.1% and identification accuracy applied to CNN is 98%.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.83-96
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• 2018

Extracting keywords representing documents is very important because it can be used for automated services such as document search, classification, recommendation system as well as quickly transmitting document information. However, when extracting keywords based on the frequency of words appearing in a web site documents and graph algorithms based on the co-occurrence of words, the problem of containing various words that are not related to the topic potentially in the web page structure, There is a difficulty in extracting the semantic keyword due to the limit of the performance of the Korean tokenizer. In this paper, we propose a method to select candidate keywords based on semantic similarity, and solve the problem that semantic keyword can not be extracted and the accuracy of Korean tokenizer analysis is poor. Finally, we use the technique of extracting final semantic keywords through filtering process to remove inconsistent keywords. Experimental results through real web pages of small business show that the performance of the proposed method is improved by 34.52% over the statistical similarity based keyword selection technique. Therefore, it is confirmed that the performance of extracting keywords from documents is improved by considering semantic similarity between words and removing inconsistent keywords.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.5
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• pp.1-11
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• 2016

There has been an increasingly high interest in gardens and garden design in Korea recently. However, the usage of the term 'garden' is extremely varied and complex, and there has been very little academic research made on the meaning of garden. Therefore, this research attempts to investigate the ideas of current gardens and to elucidate their changing patterns by means of extensive literature research and big data analysis. The notion of garden in the past was broad including not only private space such as Madang(마당) and Teul(뜰), but also even field and grass land as public outdoor space. Yet, the meaning has become smaller to merely private space due to the change of dwelling systems due to high industrial development of the 20th century. Furthermore, the introduction of urban parks as an interactive space between nature and humans, the similar spatial function of gardens, has blurred the boundary between garden and park, which created confusion in understanding the concept of a garden. After all, garden is a subject for humans. The meanings of garden need to be recognized from various points of view since garden itself is a creation by the sum of diverse fields such as natural and social sciences as well as culturology. This discussion on the meaning of garden in the present day will give a conceptual foundation for future research on gardens and garden design. Also, the big data analysis employed here as a research method can help other similar research topics, particularly semantics in landscape architecture.