• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1161-1170
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• 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 Digital Convergence
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• v.17 no.7
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• pp.27-34
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• 2019

The IT industry has made rapid development and also had an economic impact on other industries Also, since the fourth industrial revolution has begun in recent years ago, so The convergence between IT and other industries is increasing. Therefore, the development of the IT industry will enhance the international competitiveness It will also have a major impact on the nation's economic growth. Therefore, IT firms should be more efficient in their production. so This paper analyzes the efficiency of High-growth IT firms using DEA model. We evaluate the CCR, BBC efficiency and RTS(return to scale) of 12 IT firms. As a result, there were 6 companies with BCC efficiency 1 and 4 companies with 1 CCR efficiency. The scale of profitability was analyzed by IRS as 7 companies and CRS as 5 companies. We also suggest the IT firms which can be benchmarked based on analyzed information. It is expected to provide investors and external stakeholders with very useful information on managerial management efficiency.

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

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.53-77
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• 2015

Korea has witnessed an increasing number of domestic patent applications, but a majority of them are not utilized to their maximum potential but end up becoming obsolete. According to the 2012 National Congress' Inspection of Administration, about 73% of patents possessed by universities and public-funded research institutions failed to lead to creating social values, but remain latent. One of the main problem of this issue is that patent creators such as individual researcher, university, or research institution lack abilities to commercialize their patents into viable businesses with those enterprises that are in need of them. Also, for enterprises side, it is hard to find the appropriate patents by searching keywords on all such occasions. This system proposes a patent recommendation system that can identify and recommend intellectual rights appropriate to users' interested fields among a rapidly accumulating number of patent assets in a more easy and efficient manner. The proposed system extracts core contents and technology sectors from the existing pool of patents, and combines it with secondary social knowledge, which derives from tags information created by users, in order to find the best patents recommended for users. That is to say, in an early stage where there is no accumulated tag information, the recommendation is done by utilizing content characteristics, which are identified through an analysis of key words contained in such parameters as 'Title of Invention' and 'Claim' among the various patent attributes. In order to do this, the suggested system extracts only nouns from patents and assigns a weight to each noun according to the importance of it in all patents by performing TF-IDF analysis. After that, it finds patents which have similar weights with preferred patents by a user. In this paper, this similarity is called a "Domain Similarity". Next, the suggested system extract technology sector's characteristics from patent document by analyzing the international technology classification code (International Patent Classification, IPC). Every patents have more than one IPC, and each user can attach more than one tag to the patents they like. Thus, each user has a set of IPC codes included in tagged patents. The suggested system manages this IPC set to analyze technology preference of each user and find the well-fitted patents for them. In order to do this, the suggeted system calcuates a 'Technology_Similarity' between a set of IPC codes and IPC codes contained in all other patents. After that, when the tag information of multiple users are accumulated, the system expands the recommendations in consideration of other users' social tag information relating to the patent that is tagged by a concerned user. The similarity between tag information of perferred 'patents by user and other patents are called a 'Social Simialrity' in this paper. Lastly, a 'Total Similarity' are calculated by adding these three differenent similarites and patents having the highest 'Total Similarity' are recommended to each user. The suggested system are applied to a total of 1,638 korean patents obtained from the Korea Industrial Property Rights Information Service (KIPRIS) run by the Korea Intellectual Property Office. However, since this original dataset does not include tag information, we create virtual tag information and utilized this to construct the semi-virtual dataset. The proposed recommendation algorithm was implemented with JAVA, a computer programming language, and a prototype graphic user interface was also designed for this study. As the proposed system did not have dependent variables and uses virtual data, it is impossible to verify the recommendation system with a statistical method. Therefore, the study uses a scenario test method to verify the operational feasibility and recommendation effectiveness of the system. The results of this study are expected to improve the possibility of matching promising patents with the best suitable businesses. It is assumed that users' experiential knowledge can be accumulated, managed, and utilized in the As-Is patent system, which currently only manages standardized patent information.

• Management & Information Systems Review
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• v.33 no.1
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• pp.191-217
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• 2014

The Purpose of this study is to find the effect factors of R&D investment in SMEs which plays an important role in the national economy, and the differences of the effect factors by the type of SMEs. The subject of this study is about 3,400 SMEs mentioned in "The survey of technical statistics on SMEs in 2007" by Korea Federation of Small and Medium Business. The effect factors are related with the size of business, the infrastructure of R&D and the activities of R&D which have been studied by many researchers. The methods of analysis are regression analysis, moderating effect analysis and the software package used is SPSS 12.0. The results of the study are as fallow. First, it was found that unlike in previous studies which show the effect of the elements of business's size, research infrastructure, research activities on R&D investment, one element alone can't be considered for meaningful result but the various elements have effect on R&D investment at the same time. In other words, the number of employees and the sales as the elements of business's size, the ratio of researchers, the technical ability, the ratio of equipment possession and the intellectual properties as the elements of R&D infrastructure, the activity of ideas and joint research as the elements of R&D activities have positive(+) effect, whereas the participation of CEO in the activity of R&D as the elements of R&D activities activity has negative(-) one. The number of employees, the ratio of researchers, and the sales had relatively high influence whereas equipment possession, technical ability, intellectual properties, the participation of CEO in the research, the activity of idea, joint research had relatively low influence. Next, it was also found that there are differences of the effect factors over the types of SMEs. SMEs were classified into 19 types by eight criteria such as start-ups and existing business by business age; small business and medium business by size; manufacturing business and service business by product type;independent business and subcontractor business by dealing type; businesses in the entering, growing, maturing and restructuring stage by growth stage; businesses with low, medium and high technology by technological level; pioneering business and non-pioneering business by industrial type; and businesses with state-of-the-art technology and non-advanced business by the level of business activities. The meaning of this study lies in the fact that it found the various effect factors should be considered at the same time when conducting study on SMEs' R&D investment, and the differences by the type should be acknowledged. This study surpassed the limitations of the previous studies which focused on a couple of factors and types. This study result can also be considered for other studies on achievement, organization, marketing and others. Moreover, it shows that a differential policy by business type is needed when formulating SME policy.