• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of the Korean Society for information Management
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• v.23 no.1 s.59
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• pp.221-241
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• 2006

This research suggested a new patent index based on patent citation technique using cited information, For this purpose, comparison research on library and patent information related citation database providing citation index was done. The information quality and meaning on the impact factor of JCR and the technology factor of CHI were reinterpreted. The former emphasizes the quality of continuous publication using relative citation frequency. The latter only emphasizes the information itself because it assesses the quality of patent characteristics. To overcome these difficulties, the latter re-authorized a relative quality to the organization possessing the patent using technology impact factor. Three new patent index were proposed on the basis of cited information to complement this. However, the comparative object was limited to American patent information that presented cited information of patent applied cases, and the comparison and research of domestic patent information could not be done.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.559-569
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• 2022

Infrastructure engineering is a field that supports construction (assembly) as a representative industry that creates high added value and jobs by combining science and technology with knowledge, though its importance is underestimated. According to a report from the Ministry of Land, Infrastructure and Transport (Korea), the value-added rate (65.3%) of the engineering industry and the employment inducement coefficient (14 employees per billion won) are three times higher than in manufacturing. In particular,the forward value chain (such as project management and basic design) accounts for less than 10~15% of the total project cost but determines the overall price and quality of the infrastructure facilities. In this study, a work break-down system, design support module and database development method for road design projects for design platform development is presented. Based on the presented development method, a cloud-based infrastructure design platform's prototype is developed. The developed infrastructure engineering platform is expected to provide a web-based design work environment without time/space restrictions and greatly contribute to winning overseas business orders and securing competitiveness.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2011.04a
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• pp.325-329
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• 2011

Fire has developed from the inter-action of heat at the early state and it is very difficult to estimate the magnitude of the fire. Cone Calorimeter can obtain the important material properties from the exposed part of it. It can be contained that ignition, loss of mass, heat release rate, smoke generation, and gas analysis. The purpose of this study is emphasize on the properties of structural steels in terms of physical, mechanical and that will be important way to build the databases of fire safety.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.545-552
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• 2004

Association rules mining, which is one of data mining technologies, searches data among which are frequent and related to each other in database. But, although the data are not of frequent and rare in database, they have the enough worth of business information if the data ares important and strongly related to each other, In this paper, we propose the algorithm discovering association rules that consist of data, which are rare but, important and strongly related to each other in database. The proposed algorithm was evaluated through simulation. We found that the proposed algorithm discovered efficiently association rules among data, which are not frequent but, important.

• Journal of Energy Engineering
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• v.13 no.3
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• pp.191-198
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• 2004

Korea Research Reactor (KRR) 1 & 2 has shut down and through preparatory activities, its decommissioning activities are underway. As its decommissioning activities have been done over several years, its relevant data have been spreaded with various type and media all over the discrete place and inadvertently managed. As s result, managing and assessing data of KRR 1 & 2 has been difficult and complex and its data cannot be evaluated. By developing the decommissioning database system of KRR 1 & 2, the data of decommissioning activities fan be correctly evaluated, being systematically managed and objectively assessed. Finally, the decommissioning project of KRR 1 & 2 have come to more effectively accomplished.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.289-293
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• 2009

Patent information has a great value of industrial information as well as technical information. However, Korean patent information loses the effectiveness by the lack of description rule and requires much additional efforts to use them in variety. In this paper, some examples of the studies on the problems in databases were introduced and patent application(from Jan. 2008 to Oct. 2008) data retrieved from information service system of KISTI(Korea Institute of Science and Technology Information) and KIPI(Korea Institute of Patent Information) was surveyed.

• Journal of the Korea Society of Computer and Information
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• v.4 no.2
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• pp.88-94
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• 1999

Database Marketing is a technique where you use all the information available within your companies databases as well as any useful external information to either improve or enhance your marketing efforts. or on the other hand evaluate new markets or the potential of new products, that you plan to launch. Database Marketing in itself is a very simple and straight-oriented concept. Database marketing offers your company many benefits. First, marketing funds are spent cost effectively because they are concentrated on your current customers and very best prospects. Second, your company can improve its relationship with customers thereby increasing customer loyalty. Third, a marketing database provides valuable information regarding customers and prospects. Now that we are in the Information Age, a great marketing database will increase the net value of your company.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.04a
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• pp.1190-1195
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• 2000

상거래의 의미가 곧 전자상거래로 대변될 만큼 전자상거래의 전성기를 맞이하고 있으며 국내도 예외는 아니다. 전자상거래방식을 기초로 하는 인터넷 경매는 경매인과 입찰자의 상호의사표현을 통한 거래를 인터넷으로 하는 것을 말한다. 인터넷 경매에 있어서 에이전트는 입찰자, 경매인, 중개인의 경매 참여자를 대신하여 업무를 대행해주거나 결정을 도와주는 소프트웨어라고 정의할 수 있다. 기존 인터넷 경매에서의 에이전트는 단순한 검색기능과 광고만을 대행하고 있고, 경매인이 물품등록을 하고자 할 때, 주관적인 가치평가에 의해 경매시작가를 결정해야 한다. 이러한 경매인의 주관적인 경매시작가는 높은 경매시작가로 인해 유찰이 되거나 낮은 경매시작가로 낙찰가가 낮아 불이익을 가져온다. 따라서 본 논문은 경매인이 등록하고자 하는 물품에 대한 사례 경매 데이터베이스의 경매기록을 기초로 경매시작가를 분석된 정보를 제공하는 경매 정보 시스템(Auction Information System)을 제안하고자 한다.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.