• The Journal of Society for e-Business Studies
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• v.22 no.3
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• pp.1-28
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• 2017

Today, according to the increased importance of industry-university cooperation in the knowledge-based economy, support and the number of researches involved in industry-university cooperation has also steadily increased. But it is true that profits from the outcome of patents resulting from such cooperation, such as technology transfer and royalty fees, are lower than they are supposed to be, because of excessive patents applications, although some of them have little commercial potential. Therefore, this research aims to suggest a way to analyze and recognize patents, which enable efficient industry-university cooperation and technology transfer. For the analysis, data on 1,061 patents was collected from 4 different universities. With the data, a quality-strategy matrix was arranged targeting the industry-university cooperation foundations', US patents owned by universities, text mining, and social network analysis were carried out, particularly focusing on the patents in the advanced quality technology section of the matrix. Then core key words and IPC codes were obtained and key patents were analyzed by universities. As a result of the analysis, it was found that 4 key patents, 2 key IPC codes were drawn for University H, 4 key patents, 2 key IPC codes for University K, 6 key patents, 1 key IPC code for University Y, 14 key patents, and 2 key IPC codes for University S. This research is expected to have a great significance in contributing to the invigoration of industry-university cooperation based on the analysis result on patents and IPC codes, which enable efficient industry-university cooperation and technology transfer.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.9-16
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• 2018

In this paper, we propose wide range of categorizes Artificial Intelligence technology as Learning, Inference, and Cognitive. Also, it analyzes 758 cases of open patents. For an analysis, target technologies were selected and categorized into specific areas to collect information about the patents. After removing noise, the patent information for each technology such as patent assignees and IPC code, was analyzed to evaluate the maturity of technology, the way ahead for research and development and the trends in core technology. This research presents directions of Artificial intelligence technology research and trend analysis of core Artificial Intelligent technology using quantitative analysis of patent information. Also Artificial intelligence technology requires technological development necessity through close cooperation in diverse fields.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.2
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• pp.321-341
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• 2020

This study analyzed the domestic patent trends of brassiere to provide fundamental data for promising technology. Relevant patents were searched by inputting the key words of "brassiere" and IPC code "A41C" on patent information search service of KIPRIS. A search for bras patents from 1985 to 2019 revealed 533 registered applications out of the total 744 listed. The IPC code with the highest portion (40%) was A41C3/00 (brassiere), followed by A41C3/14 (forming inserts, 21.6%), and A41C3/12 (component parts, 13.3%). To arrange the guidelines of the content of brassiere patents, we carried out a qualitative technology analysis on 744 patents, to extract 850 technology cases applied in patents. From the technological features of each case, main categories were classified into two parts (function and structure) and function was divided into 7 sub-categories that included physiological comfort, physical comfort, utility, healthcare, appearance, and economic value. As for the structure, cup showed the highest portion (37.9%), followed by pad (16.5%), and wings (13.2%). From the aspect of function, appearance showed the highest portion (30.8%), followed by usability (22.2%), physiological comfort (14.6%), physical comfort (14.6%), economic value (10.7%), and health care (7.4%).

• Fashion & Textile Research Journal
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• v.16 no.1
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• pp.160-166
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• 2014

Patent and utility indicate international competitiveness in the knowledge-based society of the $21^{st}$century where both the quantity and quality of the nation's scientific intelligence and innovative technology represent key criteria to evaluate its strength. Thus, discerning the trends of patents is inevitable for further development. This research is centered on apprehending the technological current of the functional clothing of Korea, through an analysis of patents and utility models. The number of patent applications in Korea was low until the mid-1990s. However, it began to grow rapidly in the 2000s and the number of patents surpassed the number of utility starting in 2006. The technological level of invention in this field has been turned into a higher level. The IPC code with the strongest application was the field related to temperature controllable clothing (A41D 13/005), followed by surgeon or patient apparel related fields (A41D 13/12), and reflective or luminous safety devices (A41D 13/01).The main technological idea was to give functionality that could protect the human body from various hazards and represents the goal of various applied techniques. About 66% of domestic patent applications belong to individuals; however, the proportion of corporate or institutional applications(including universities) remains poor. Consequently, more systematic and long-term support for research on patents is required.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.392-397
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• 2015

Society has been developed through analogue, digital, and smart era. Every technology is going through consistent changes and rapid developments. In this competitive society, R&D strategy establishment is significantly useful and helpful for improving technology competitiveness. A patent document includes technical and legal rights information such as title, abstract, description, claim, and patent classification code. From the patent document, a lot of people can understand and collect legal and technical information. This unique feature of patent can be quantitatively applied for technology analysis. This research paper proposes a methodology for extracting core technology and patents based on quantitative methods. Statistical analysis and social network analysis are applied to IPC codes in order to extract core technologies with active R&D and high centralities. Then, core patents are also extracted by analyzing citation and family information.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.53-58
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• 2024

This study is about the technology convergence analysis of e-commerce related patents containing Artificial Intelligence applied for in Korea. The relationships between core technologies were analyzed and visualized using social network analysis. As a result of social network analysis, the core IPC codes that make up the mutual technology network in e-commerce related patents containing Artificial Intelligence were found to be G06Q, G06F, G06N, G16H, G10L, H04N, G06T, and A61B. In particular, it can be confirmed that there is an important convergence of data processing-related technologies such as [G06Q-G06F], [G06Q-G06N], and voice and image signals such as [G06Q-G10L], [G06Q-H04N], and [G06Q-G06T]. Using this research method, it is possible to identify future technology trends in e-commerce related patents and create new Business Models.

• Journal of Digital Contents Society
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• v.19 no.3
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• pp.529-535
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• 2018

Data is explosively growing, but many companies are still using data analysis only for descriptive analysis or diagnostic analysis, and not appropriately for predictive analysis or enterprise technology strategy analysis. In this study, we analyze the structured & unstructured patent data such as IPC code, inventor, filing date and so on by using big data analysis techniques such as network analysis and TF-IDF. Through this analysis, we propose analysis process to understand the core technology and technology distribution of competitors and prove it through data analysis.

• The Korean Journal of Community Living Science
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• v.26 no.4
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• pp.647-659
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• 2015

This study analyzes current technologies in personal protective equipment (PPE) and mechanisms that can be used in the agricultural field to provide data for research and development on PPE for farmers. There is growing awareness of the importance of PPE as part of efforts to reduce agricultural accidents, but data remain rare for developing PPE tailored to the farm work environment. In this regard, patent data on PPE can provide useful insights for facilitating relevant technologies and research. This study examines patents and utility models classified under the IPC code in Korea and other countries to analyze patented technologies and recent trends for the period from January 2003 to October 2014. Here Korea, the U.S., Japan, and Europe were considered. The results show that the number of patent applications for PPE remained steady without any sharp fluctuations. KIPO applications accounted for 43.5% of all cases, reflecting the highest proportion among the countries considered. Domestic applicants accounted for 94% of all cases. In Korea, patent applications were concentrated in safety gear for the face and eyes, indicating a high level of technology. The highest level of competition was observed for safety goggles in all countries. Some PPE technologies were dominated by a particular manufacturer. The analysis results for farming-related technologies show the current state of technologies and areas lacking technological development. This study analyzes patented technologies for PPE in Korea and other countries and recent research trends as part of the effort to develop PPE for workers in the farming and livestock industry. This study represents an early-stage effort to develop PPE for workers in the farming and livestock industry, and the results are expected to be useful for tailoring PPE to Korea's farming and livestock 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.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.221-241
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• 2018

As we enter the knowledge society, the importance of information as a new form of capital is being emphasized. The importance of information classification is also increasing for efficient management of digital information produced exponentially. In this study, we tried to automatically classify and provide tailored information that can help companies decide to make technology commercialization. Therefore, we propose a method to classify information based on Korea Standard Industry Classification (KSIC), which indicates the business characteristics of enterprises. The classification of information or documents has been largely based on machine learning, but there is not enough training data categorized on the basis of KSIC. Therefore, this study applied the method of calculating similarity between documents. Specifically, a method and a model for presenting the most appropriate KSIC code are proposed by collecting explanatory texts of each code of KSIC and calculating the similarity with the classification object document using the vector space model. The IPC data were collected and classified by KSIC. And then verified the methodology by comparing it with the KSIC-IPC concordance table provided by the Korean Intellectual Property Office. As a result of the verification, the highest agreement was obtained when the LT method, which is a kind of TF-IDF calculation formula, was applied. At this time, the degree of match of the first rank matching KSIC was 53% and the cumulative match of the fifth ranking was 76%. Through this, it can be confirmed that KSIC classification of technology, industry, and market information that SMEs need more quantitatively and objectively is possible. In addition, it is considered that the methods and results provided in this study can be used as a basic data to help the qualitative judgment of experts in creating a linkage table between heterogeneous classification systems.