• Journal of Technology Innovation
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• v.23 no.3
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• pp.201-223
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• 2015

Existing research on international standardization has largely taken a qualitative approach focusing on comparative studies of national institutions and policies on standards or international rivalries from the perspectives of international relations or innovation studies. While there exists a handful of quantitative studies, they are mostly confined to simple numeric counts of essential patents, new work item proposals, or secretaries staffing international standards development organizations (SDOs). This study aims to contribute to our understanding of the dynamics of international standardization by the analysis of the data coding systematically national activities in the standardization process of the International Organization for Standardization (ISO), by far the largest international SDO. Our analysis of the four critical types of standardization documents generated in the Working Group 7 of the ISO/IEC Joint Technical Committee 1 reveals interesting dynamics among key players of global ICT standards regime. First, while the US takes a dominant share of the personnel as well as new work item proposals for standardization, its quality of activities rather falls behind as it mostly focuses on keeping in check other countries' standardization activities. Second, European countries tend to spread their effort evenly across different types of standardization activities. Finally, despite such differences between the US and European countries, both rely heavily on multinational companies to gain an advantage in the voting stage of standardization process.

• Journal of Technology Innovation
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• v.20 no.1
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• pp.199-234
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• 2012

Technology roadmaps (TRMs) are considered to be the essential tool for strategic technology planning and management. Recently, rapidly evolving technological trends and severe technological competition are making TRM more important than ever before. That is because TRM plays a role of "map" that align organizational objectives with their relevant technologies. However, constructing and managing TRMs are costly and time-consuming because they rely on the qualitative and intuitive knowledge of human experts. Therefore, enhancing the productivity of developing TRMs is one of the major concerns in technology planning. In this regard, this paper proposes a technology roadmapping approach based on function of which concept includes objectives, structures and effects of a technology and which are represented as Subject-Action-Object structures extractable by exploiting natural language processing of patent text. We expect that the proposed method will broaden experts' technological horizons in the technology planning process and will help to construct TRMs efficiently with the reduced time and costs.

• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.4
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• pp.19-28
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• 2017

Companies and Governments have Mainly used the Delphi Technique to Understand Research or Technology Trends. Because this Technique has the Disadvantage of Consuming a Large Amount of Time and Money, this Study Attempted to Understand and Predict Science and Technology Trends using the Topic Modeling Technique Latent Dirichlet Allocation (LDA). To this end, 20 Specific Artificial Intelligence (AI) Technologies were Extracted From the Abstracts of the US Patent Documents on AI. With Regard to the Extracted Specific Technologies, Core Technologies were Identified, and then these were Divided into Hot and Cold Technologies though a Trend Analysis on their Annual Proportions. Text/Word Searching, Computer Management, Programming Syntax, Network Administration, Multimedia, and Wireless Network Technology were Derived From Hot Technologies. These Technologies are Key Technologies that are Actively Studied in the Field of AI in Recent Years. The Methodology Suggested in this Study may be used to Analyze Trends, Derive Policies, or Predict Technical Demands in Various Fields such as Social Issues, Regional Innovation, and Management.

• Annual Conference on Human and Language Technology
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• 2005.10a
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• pp.13-20
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• 2005

이 논문은 공학적인 접근 방법에 기반한 단계적인 전문분야 시소러스 구축 방법을 제안한다. 시소러스 구축 과정은 용어 추출 단계, 용어 분류 단계, 계층 구조 구축 의 3단계로 구성되고, 모든 단계에서 자동 처리와 전문가 검증 작업을 거친다. 추출된 용어를 미리 정해진 분류 체계에 따라 분리한 후 여러 개의 작은 시소러스를 구축하고, 마지막으로 전체 시소러스로 결합한다. 이 방법은 1) 시소러스를 구축하는 복잡도가 줄어들고, 2) 클래스 단위의 작은 시소러스가 다른 전문분야 시소러스에 쉽게 재사용 될 수 있으며, 3) 각 클래스에 포함된 용어들의 분포를 쉽게 판단할 수 있는 장점이 있다. 제안한 방법을 이용하여 한국어 정보기술 분야 시소러스를 구축하였다. 시소러스 구축에 사용된 용어들은 정보기술 분야의 최근의 한국어 신문과 특허 문서에서 추출하였기 때문에 한국에서 만들어진 신조어를 포함한다. 구축된 시소러스는 81 개의 상위 레벨클래스와 1,000개 이상의 용어로 구성된다.

• Journal of the Korea Safety Management & Science
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• v.17 no.4
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• pp.335-342
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• 2015

The increasing interests on patents have led many individuals and companies to apply for many patents in various areas. Applied patents are stored in the forms of electronic documents. The search and categorization for these documents are issues of major fields in data mining. Especially, the keyword extraction by which we retrieve the representative keywords is important. Most of techniques for it is based on vector space model. But this model is simply based on frequency of terms in documents, gives them weights based on their frequency and selects the keywords according to the order of weights. However, this model has the limit that it cannot reflect the relations between keywords. This paper proposes the advanced way to extract the more representative keywords by overcoming this limit. In this way, the proposed model firstly prepares the candidate set using the vector model, then makes the graph which represents the relation in the pair of candidate keywords in the set and selects the keywords based on this relationship graph.

• 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.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.1-18
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• 2021

ICT is the main driving force of Korea's economic growth. Korea has the world's best ICT competitiveness, and several policies are being implemented to maintain it. However, for successful policy implementation, it is crucial to understand ICT trends accurately. Therefore, this study analyzes the trends of 18 core technologies in the ICT field. In particular, the degree of scientific development and commercialization by technology are investigated through research paper analysis and patent analysis, respectively. Then, the trends shown by document type are compared based on the two analysis results. As a result, artificial intelligence and virtual reality are at the stage where commercialization is actively taking place after scientific development, and at the same time, since research is being conducted, it is expected to develop continuously. On the other hand, quantum computer and implantable device are in the basic research stage. It is necessary to understand the current research status and determine the direction of future support. The results of the ICT trend analysis conducted in this study can be used as a criterion for determining the future direction of Korean policy.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.297-304
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• 2010

Clustering method which based on sentence type or document genre is a technique used to improve translation quality of SMT(statistical machine translation) by domain-specific translation. But there is no previous research using sentence type and document genre information simultaneously. In this paper, we suggest an integrated clustering method that classifying sentence type by syntactic structure similarity and document genre by word similarity information. We interpolated domain-specific models from clusters with general models to improve translation quality of SMT system. Kernel function and cosine measures are applied to calculate structural similarity and word similarity. With these similarities, we used machine learning algorithms similar to K-means to clustering. In Japanese-English patent translation corpus, we got 2.5% point relative improvements of translation quality at optimal case.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.17 no.2
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• pp.157-176
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• 2006

This study covers the transition of the records and archives management system of Won-Buddhism. The System can be reviewed in four eras. In the Bulbeopyeonguhoe regulations era(1924$\sim$1948), records and archives were managed in an elementary but more ingenious manner than in any other era. The first phase of the Won-Buddhism regulations era(1948$\sim$1965) was governed by the Won-Buddhism Regulations, though the traditional system of the Bulbeopyeonguhoe regulations era was still widely practiced. During the second phase of the Won-Buddhism regulations era (1965$\sim$1994), the system of "national regulations" was actively introduced into the Won-Buddhism system of managing records and archives. During the third phase of the Won-Buddhism regulations era(1994$\sim$present), the Won-Buddhism Regulations had their own meaning because in that they were the first regulations of Won-Buddhism established for the sole purpose of managing records and archives. This study has significance for understanding the Won-Buddhism system of managing records and archives.