• Title/Summary/Keyword: Language modeling

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Development and Utilization of Linked Data of Port Maintenance Information for Port Facilities Based on Port BIM Standards (항만 BIM 표준 기반 항만 유지관리 정보의 링크드데이터 구축 및 활용)

  • Shin, Jaeyoung;Moon, Hyounseok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.4
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    • pp.501-510
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    • 2023
  • The importance of using construction data is increasing in accordance with the recent trend in the smart construction. However, construction project and maintenance information is distributed on the web, and the existing BIM(Building Information Modeling) information exchange and linking method using IFC(Industry Foundation Classes) cannot support connection with BIM data and web resources. This study aims to establish the BIM-based port facility data integration system using linked data(LD) technology in order to integrate BIM and heterogeneous data in the port maintenance domain. To this end, the port BIM-based ifcOWL and port facility maintenance ontology were designed, and LD was built for the BIM and maintenance information of Busan New Port 2-1 Pier3, a BIM pilot project. In addition, service prototypes such as search, statistics and SPARQL(SPARQL Protocol and RDF Query Language) endpoint functions were implemented using the issued LD. The LD-based information utilization system is expected to improve the reusability of information by converting the existing closed information system into an open system and BIM and maintenance data as a web resource in a standard format.

Development and application of automation algorithm for optimal parameter combination in two-dimensional flow analysis model (2차원 흐름해석모형의 매개변수 최적조합결정 자동화 알고리즘의 개발과 적용)

  • An, Sehyuck;Shin, Eun-taek;Song, Chang Geun;Park, Sungwon
    • Journal of Korea Water Resources Association
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    • v.56 no.spc1
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    • pp.1007-1014
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    • 2023
  • Two-dimensional flow analysis, a fundamental component of hydrodynamics, plays a pivotal role in numerically simulating fluid behavior in rivers and waterways. This modeling approach heavily relies on parameters such as eddy viscosity and roughness coefficient to accurately represent flow characteristics. Therefore, combination of appropriate parameters is very important to accurately simulate flow characteristics. In this study, an automation algorithm was developed and applied to find the optimal combination of parameters. Previously, when applying a two-dimensional flow analysis model, former researchers usually depend on the empirical approach, which causes many difficulties in finding optimal variable values. Using the experimental data, we tracked errors according to the combination of various parameters and applied the algorithm that can determine the optimal combination of parameters with the Python language. The automation algorithm can easily determine the most accurate combination by comparing the flow velocity error values among the two-dimensional flow analysis results among the combinations of 121 (11×11) parameters. In the perspective of utilizing automation algorithm, there is an expected high utility in promptly and straightforwardly determining the optimal combination of parameters with the smallest error.

Analysis of the Impact of Generative AI based on Crunchbase: Before and After the Emergence of ChatGPT (Crunchbase를 바탕으로 한 Generative AI 영향 분석: ChatGPT 등장 전·후를 중심으로)

  • Nayun Kim;Youngjung Geum
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.19 no.3
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    • pp.53-68
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    • 2024
  • Generative AI is receiving a lot of attention around the world, and ways to effectively utilize it in the business environment are being explored. In particular, since the public release of the ChatGPT service, which applies the GPT-3.5 model, a large language model developed by OpenAI, it has attracted more attention and has had a significant impact on the entire industry. This study focuses on the emergence of Generative AI, especially ChatGPT, which applies OpenAI's GPT-3.5 model, to investigate its impact on the startup industry and compare the changes that occurred before and after its emergence. This study aims to shed light on the actual application and impact of generative AI in the business environment by examining in detail how generative AI is being used in the startup industry and analyzing the impact of ChatGPT's emergence on the industry. To this end, we collected company information of generative AI-related startups that appeared before and after the ChatGPT announcement and analyzed changes in industry, business content, and investment information. Through keyword analysis, topic modeling, and network analysis, we identified trends in the startup industry and how the introduction of generative AI has revolutionized the startup industry. As a result of the study, we found that the number of startups related to Generative AI has increased since the emergence of ChatGPT, and in particular, the total and average amount of funding for Generative AI-related startups has increased significantly. We also found that various industries are attempting to apply Generative AI technology, and the development of services and products such as enterprise applications and SaaS using Generative AI has been actively promoted, influencing the emergence of new business models. The findings of this study confirm the impact of Generative AI on the startup industry and contribute to our understanding of how the emergence of this innovative new technology can change the business ecosystem.

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Rediscovering the Interest of Science Education: Focus on the Meaning and Value of Interest (과학교육의 재미에 대한 재발견 -재미의 의미와 가치를 중심으로-)

  • Shin, Sein;Ha, Minsu;Lee, Jun-Ki
    • Journal of The Korean Association For Science Education
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    • v.38 no.5
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    • pp.705-720
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    • 2018
  • The purpose of this study is to shed light on the meaning and value of interest (in Korean 'Jae-mi') in science education through literature analysis. Literature analyses were conducted on literature related to interest in various fields such as Korean language, psychology, philosophy, and education. Specifically, this study discussed the meaning of interest, the characteristics of the context of experiencing interest, the educational value of interest in science education, and the direction of science education to realize the value of interest. First, it was found that interest is an experience of emotional activation that can be felt through interaction with a specific object, and it is an emotional experience caused by the complex combination of various psychological factors, which is oriented sense, relationship, self, and object. Second, to understand the context of experience of interest, we conducted a topic modeling analysis with 1173 research articles related to interest. As a result of the analysis, it was confirmed that the context of interest is closely related with playfulness. And we addressed that this kind of playfulness is also found in science. Third, the educational values of interest in science education were discussed. In science education, fun is not only an instrumental value to induce science learning behavior, it is also one of the universal experiences that learners feel lively in science teaching-learning, and driving force of individual students' emotional development related to science. The students' active attitude to feel interest lead to creative thinking and action. Finally, we argued that the interest that should be aimed in science education should be active interest and experienced at trial and error, not passive interest induced by external stimuli. And science education culture should be encouraged to respect those who enjoy science. In particular, this study discussed the importance of each student's unique interest experience based on the philosophy of philosopher Deleuze (1976).

A study on detective story authors' style differentiation and style structure based on Text Mining (텍스트 마이닝 기법을 활용한 고전 추리 소설 작가 간 문체적 차이와 문체 구조에 대한 연구)

  • Moon, Seok Hyung;Kang, Juyoung
    • Journal of Intelligence and Information Systems
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    • v.25 no.3
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    • pp.89-115
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    • 2019
  • This study was conducted to present the stylistic differences between Arthur Conan Doyle and Agatha Christie, famous as writers of classical mystery novels, through data analysis, and further to present the analytical methodology of the study of style based on text mining. The reason why we chose mystery novels for our research is because the unique devices that exist in classical mystery novels have strong stylistic characteristics, and furthermore, by choosing Arthur Conan Doyle and Agatha Christie, who are also famous to the general reader, as subjects of analysis, so that people who are unfamiliar with the research can be familiar with them. The primary objective of this study is to identify how the differences exist within the text and to interpret the effects of these differences on the reader. Accordingly, in addition to events and characters, which are key elements of mystery novels, the writer's grammatical style of writing was defined in style and attempted to analyze it. Two series and four books were selected by each writer, and the text was divided into sentences to secure data. After measuring and granting the emotional score according to each sentence, the emotions of the page progress were visualized as a graph, and the trend of the event progress in the novel was identified under eight themes by applying Topic modeling according to the page. By organizing co-occurrence matrices and performing network analysis, we were able to visually see changes in relationships between people as events progressed. In addition, the entire sentence was divided into a grammatical system based on a total of six types of writing style to identify differences between writers and between works. This enabled us to identify not only the general grammatical writing style of the author, but also the inherent stylistic characteristics in their unconsciousness, and to interpret the effects of these characteristics on the reader. This series of research processes can help to understand the context of the entire text based on a defined understanding of the style, and furthermore, by integrating previously individually conducted stylistic studies. This prior understanding can also contribute to discovering and clarifying the existence of text in unstructured data, including online text. This could help enable more accurate recognition of emotions and delivery of commands on an interactive artificial intelligence platform that currently converts voice into natural language. In the face of increasing attempts to analyze online texts, including New Media, in many ways and discover social phenomena and managerial values, it is expected to contribute to more meaningful online text analysis and semantic interpretation through the links to these studies. However, the fact that the analysis data used in this study are two or four books by author can be considered as a limitation in that the data analysis was not attempted in sufficient quantities. The application of the writing characteristics applied to the Korean text even though it was an English text also could be limitation. The more diverse stylistic characteristics were limited to six, and the less likely interpretation was also considered as a limitation. In addition, it is also regrettable that the research was conducted by analyzing classical mystery novels rather than text that is commonly used today, and that various classical mystery novel writers were not compared. Subsequent research will attempt to increase the diversity of interpretations by taking into account a wider variety of grammatical systems and stylistic structures and will also be applied to the current frequently used online text analysis to assess the potential for interpretation. It is expected that this will enable the interpretation and definition of the specific structure of the style and that various usability can be considered.

Analysis on Dynamics of Korea Startup Ecosystems Based on Topic Modeling (토픽 모델링을 활용한 한국의 창업생태계 트렌드 변화 분석)

  • Heeyoung Son;Myungjong Lee;Youngjo Byun
    • Knowledge Management Research
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    • v.23 no.4
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    • pp.315-338
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    • 2022
  • In 1986, Korea established legal systems to support small and medium-sized start-ups, which becomes the main pillars of national development. The legal systems have stimulated start-up ecosystems to have more than 1 million new start-up companies founded every year during the past 30 years. To analyze the trend of Korea's start-up ecosystem, in this study, we collected 1.18 million news articles from 1991 to 2020. Then, we extracted news articles that have the keywords "start-up", "venture", and "start-up". We employed network analysis and topic modeling to analyze collected news articles. Our analysis can contribute to analyzing the government policy direction shown in the history of start-up support policy. Specifically, our analysis identifies the dynamic characteristics of government influenced by external environmental factors (e.g., society, economy, and culture). The results of our analysis suggest that the start-up ecosystems in Korea have changed and developed mainly by the government policies for corporation governance, industrial development planning, deregulation, and economic prosperity plan. Our frequency keyword analysis contributes to understanding entrepreneurial productivity attributed to activities among the networked components in industrial ecosystems. Our analyses and results provide practitioners and researchers with practical and academic implications that can help to establish dedicated support policies through forecast tasks of the economic environment surrounding the start-ups. Korean entrepreneurial productivity has been empowered by growing numbers of large companies in the mobile phone industry. The spectrum of large companies incorporates content startups, platform providers, online shopping malls, and youth-oriented start-ups. In addition, economic situational factors contribute to the growth of Korean entrepreneurial productivity the economic, which are related to the global expansions of the mobile industry, and government efforts to foster start-ups. Our research is methodologically implicative. We employ natural language processes for 30 years of media articles, which enables more rigorous analysis compared to the existing studies which only observe changes in government and policy based on a qualitative manner.

Twitter Issue Tracking System by Topic Modeling Techniques (토픽 모델링을 이용한 트위터 이슈 트래킹 시스템)

  • Bae, Jung-Hwan;Han, Nam-Gi;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.109-122
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    • 2014
  • People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

Development of the Information Delivery System for the Home Nursing Service (가정간호사업 운용을 위한 정보전달체계 개발 I (가정간호 데이터베이스 구축과 뇌졸중 환자의 가정간호 전산개발))

  • Park, J.H;Kim, M.J;Hong, K.J;Han, K.J;Park, S.A;Yung, S.N;Lee, I.S;Joh, H.;Bang, K.S
    • Journal of Home Health Care Nursing
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    • v.4
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    • pp.5-22
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    • 1997
  • The purpose of the study was to development an information delivery system for the home nursing service, to demonstrate and to evaluate the efficiency of it. The period of research conduct was from September 1996 to August 31, 1997. At the 1st stage to achieve the purpose, Firstly Assessment tool for the patients with cerebral vascular disease who have the first priority of HNS among the patients with various health problems at home was developed through literature review. Secondly, after identification of patient nursing problem by the home care nurse with the assessment tool, the patient's classification system developed by Park (1988) that was 128 nursing activities under 6 categories was used to identify the home care nurse's activities of the patient with CAV at home. The research team had several workshops with 5 clinical nurse experts to refine it. At last 110 nursing activities under 11 categories for the patients with CVA were derived. At the second stage, algorithms were developed to connect 110 nursing activities with the patient nursing problems identified by assessment tool. The computerizing process of the algorithms is as follows: These algorithms are realized with the computer program by use of the software engineering technique. The development is made by the prototyping method, which is the requirement analysis of the software specifications. The basic features of the usability, compatibility, adaptability and maintainability are taken into consideration. Particular emphasis is given to the efficient construction of the database. To enhance the database efficiency and to establish the structural cohesion, the data field is categorized with the weight of relevance to the particular disease. This approach permits the easy adaptability when numerous diseases are applied in the future. In paralleled with this, the expandability and maintainability is stressed through out the program development, which leads to the modular concept. However since the disease to be applied is increased in number as the project progress and since they are interrelated and coupled each other, the expand ability as well as maintainability should be considered with a big priority. Furthermore, since the system is to be synthesized with other medical systems in the future, these properties are very important. The prototype developed in this project is to be evaluated through the stage of system testing. There are various evaluation metrics such as cohesion, coupling and adaptability so on. But unfortunately, direct measurement of these metrics are very difficult, and accordingly, analytical and quantitative evaluations are almost impossible. Therefore, instead of the analytical evaluation, the experimental evaluation is to be applied through the test run by various users. This system testing will provide the viewpoint analysis of the user's level, and the detail and additional requirement specifications arising from user's real situation will be feedback into the system modeling. Also. the degree of freedom of the input and output will be improved, and the hardware limitation will be investigated. Upon the refining, the prototype system will be used as a design template. and will be used to develop the more extensive system. In detail. the relevant modules will be developed for the various diseases, and the module will be integrated by the macroscopic design process focusing on the inter modularity, generality of the database. and compatibility with other systems. The Home care Evaluation System is comprised of three main modules of : (1) General information on a patient, (2) General health status of a patient, and (3) Cerebrovascular disease patient. The general health status module has five sub modules of physical measurement, vitality, nursing, pharmaceutical description and emotional/cognition ability. The CVA patient module is divided into ten sub modules such as subjective sense, consciousness, memory and language pattern so on. The typical sub modules are described in appendix 3.

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The Effects of Cognitive Bias on Entrepreneurial Opportunity Evaluations through Perceived Risks in Entrepreneurial Self-Efficacy (창업가의 인지편향이 지각된 위험과 조절된 창업효능감에 따라 창업기회평가에 미치는 영향)

  • Kim, Daeyop;Park, Jaehwan
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.15 no.1
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    • pp.95-112
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    • 2020
  • This paper is to investigate how cognitive bias of college students and entrepreneurs relates to perceived risks and entrepreneurial opportunities that represent uncertainty, and how various cognitive bias and entrepreneurial efficacy In the same way. The purpose of this study is to find improvement points of entrepreneurship education for college students and to suggest problems and improvement possibilities in the decision making process of current entrepreneurs. This empirical study is a necessary to improve the decision-making of individuals who want to start a business at the time when various attempts are made to activate the start-up business and increase the sustainability of the existing SME management. And understanding of the difference in opportunity evaluation, and suggests that it is necessary to provide good opportunities together with the upbringing of entrepreneurs. In order to achieve the purpose of the study, questionnaires were conducted for college students and entrepreneurs. A total of 363 questionnaire data were obtained and demonstrated through structural equation modeling. This study confirms that there is some relationship between perceived risk and cognitive bias. Overconfidence and control illusions among cognitive bias have a significant relationship between perceived risk and wealth. Especially, it is confirmed that control illusion of college students has a significant relationship with perceived risk. Second, cognitive bias demonstrated some significant relationship with opportunity evaluation. Although we did not find evidence that excess self-confidence is related to opportunity evaluation, we have verified that control illusions and current status bias are related to opportunity evaluation. Control illusions were significant in both college students and entrepreneurs. Third, perceived risk has a negative relationship with opportunity evaluation. All students, regardless of whether they are college students or entrepreneurs, judge opportunities positively if they perceive low risk. Fourth, it can be seen from the college students 'group that entrepreneurial efficacy has a moderating effect between perceived risk and opportunity evaluation, but no significant results were found in the entrepreneurs' group. Fifth, the college students and entrepreneurs have different cognitive bias, and they have proved that there is a different relationship between entrepreneurial opportunity evaluation and perceived risk. On the whole, there are various cognitive biases that are caused by time pressure or stress on college students and entrepreneurs who have to make judgments in uncertain opportunities, and in this respect, they can improve their judgment in the future. At the same time, university students can have a positive view of new opportunities based on high entrepreneurial efficacy, but if they fully understand the intrinsic risks of entrepreneurship through entrepreneurial education and fully understand the cognitive bias present in direct entrepreneurial experience, You will get a better opportunity assessment. This study has limitations in that it is based on the fact that university students and entrepreneurs are integrated, and that the survey respondents are selected by the limited random sampling method. It is necessary to conduct more systematic research based on more faithful data in the absence of the accumulation of entrepreneurial research data. Second, the translation tools used in the previous studies were translated and the meaning of the measurement tools might not be conveyed due to language differences. Therefore, it is necessary to construct a more precise scale for the accuracy of the study. Finally, complementary research should be done to identify what competitive opportunities are and what opportunities are appropriate for entrepreneurs.

A Construction of the C_MDR(Component_MetaData Registry) for the Environment of Exchanging the Component (컴포넌트 유통환경을 위한 컴포넌트 메타데이타 레지스트리 구축 : C_MDR)

  • Song, Chee-Yang;Yim, Sung-Bin;Baik, Doo-Kwon;Kim, Chul-Hong
    • Journal of KIISE:Computing Practices and Letters
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    • v.7 no.6
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    • pp.614-629
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    • 2001
  • As the information-intensive society in 21c based on the environment of global internet is promoted, the software is getting more large and complex, and the demand for the software is increasing briskly. So, it becomes an important issue in academic and industrial field to activate reuse by developing and exchanging the standardized component. Currently, the information services as a product type of each company are provided in foreign market place for reusing a commercial component, but the components which are serviced in each market place are different, insufficient and unstandardized. That is, construction for Component Data Registry based on ISO 11179, is not accomplished. Hence, the national government has stepped up the plan for sending out public component at 2001. Therefore, the systems as a tool for sharing and exchange of data, have to support the meta-information of standardized component. In this paper, we will propose the C_MDR system: a tool to register and manage the standardized meta-information, based upon ISO 11179, for the commercialized common component. The purpose of this system is to systemically share and exchange the data in chain of acceleration of reusing the component. So, we will show the platform of specification for the component meta-information, then define the meta-information according to this platform, also represent the meta-information using XML for enhancing the interoperability of information with other system. Moreover, we will show that three-layered expression make modeling to be simple and understandable. The implementation of this system is to construct a prototype system of the component meta-information through the internet on www, this system uses ASP as a development language and RDBMS Oracle for PC. Thus, we may expect the standardization of the exchanged component metadata, and be able to apply to the exchanged reuse tool.

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