• Title/Summary/Keyword: Knowledge Index

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Species Diversity Analysis of Ecosystem Survey Data Using Total Information (정보계측기법을 이용한 생태조사자료의 종다양도 분석)

  • Jung, Nam-Su;Lee, Jeong-Jae;Park, Seung-Kie;Kim, Woong
    • Journal of Korean Society of Rural Planning
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    • v.13 no.2
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    • pp.1-5
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    • 2007
  • Shannon and Simpson indexes are used for species diversity analysis of ecosystem. In species diversity analysis of ecosystem, not only frequency of each species but also survey size have to be considered. In this study, total information composed with knowledge and ignorance was suggested as a species diversity analysis method for ecosystem survey. To apply developed method, flora in the Sangachun river valley was sampled with 19 sites and 198 species. In applying results, Shannon index shows more reasonable results than Simpson index by the variance of sample size but has difficulties of determining the relation of surveying species number and sample site number. Suggested total information can overcome this difficulty by the relation of knowledge and ignorance.

A Study on the Index Model for Secondary Legal Information Databases (법률정보시스템의 색인에 관한 연구 -특히 2차 법률정보를 중심으로-)

  • 노정란
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.8 no.1
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    • pp.117-134
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    • 1997
  • This study proves that the quoted legal text functions as the index which represents the contents of the text because of the characteristics of legal information, the automatic indexing in the secondary legal full-text databases can be possible without the assitance of the experts. In case of the establishment, amendment or repealing of law, change of words of index can be possible through revising the legal text quoted in the secondary legal full-text databases. Even when we dont input the full-text about retrospective documents, automatic indexing is also possible, and the establihment and the practice of expert knowledge and integrated databases are possible in case of the retrospective documents. This study indicates that it is necessary to have characteristic information the information experts recognize - that is to say, experimental and inherent knowledge only human being can have - built-in into the system rather than to approach the information system by the linguistic, statistic or structuralistic way, and it can be more essential and intelligent information system.

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A Study of Combinative Index for Conflict Resolution (상충 해결을 위한 결합지수 연구)

  • 고희병;이수홍;이만호
    • Korean Journal of Computational Design and Engineering
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    • v.5 no.4
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    • pp.319-326
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    • 2000
  • Expert systems using uncertain and ambiguous knowledge are not of the recent interests about uncertainty problem for performing inference similar to the decision making of a human expert. Human factors on rule-based systems often involve uncertain information. Expert systems had been used the methods of conflict resolution in a rule conflict situation, but this methods not properly solved the rule conflict. If a human expert appends a new rule to an original rule base, the rule base rightly causes a rule conflict. In this paper, the problem of rule conflict is regarded as one in which uncertainty of information is fundamentally involved. In the reduction of problem with uncertainty, we propose an enhanced rule ordering method, which improve the rule ordering method using Dempster-Shafer theory. We also propose a combinative index, which involve human factors of experts decision making.

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An Evolutionary Approach to Inferring Decision Rules from Stock Price Index Predictions of Experts

  • Kim, Myoung-Jong
    • Management Science and Financial Engineering
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    • v.15 no.2
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    • pp.101-118
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    • 2009
  • In quantitative contexts, data mining is widely applied to the prediction of stock prices from financial time-series. However, few studies have examined the potential of data mining for shedding light on the qualitative problem-solving knowledge of experts who make stock price predictions. This paper presents a GA-based data mining approach to characterizing the qualitative knowledge of such experts, based on their observed predictions. This study is the first of its kind in the GA literature. The results indicate that this approach generates rules with higher accuracy and greater coverage than inductive learning methods or neural networks. They also indicate considerable agreement between the GA method and expert problem-solving approaches. Therefore, the proposed method offers a suitable tool for eliciting and representing expert decision rules, and thus constitutes an effective means of predicting the stock price index.

A Study on Developing and Refining a Large Citation Service System

  • Kim, Kwang-Young;Kim, Hwan-Min
    • International Journal of Knowledge Content Development & Technology
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    • v.3 no.1
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    • pp.65-80
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    • 2013
  • Today, citation index information is used as an outcome scale of spreading technology and encouraging research. Article citation information is an important factor to determine the authority of the relevant author. Google Scholar uses the article citation information to organize academic article search results with a rank algorithm. For an accurate analysis of such important citation index information, large amounts of bibliographic data are required. Therefore, this study aims to build a fast and efficient system for large amounts of bibliographic data, and to design and develop a system for quickly analyzing cited information for that data. This study also aims to use and analyze citation data to be a basic element for providing various advanced services to the academic article search system.

A Study of Designing the Knowledge Base System for the Query Extension by Index File (색인파일 기반의 질의어 확장용 지식베이스 구축에 관한 연구)

  • Seo, Whee
    • Journal of Korean Library and Information Science Society
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    • v.40 no.2
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    • pp.139-159
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    • 2009
  • This study is to develop knowledge base system for query extension to the user oriented information retrieval. This study has survey the theories of the concept-based information retrieval method and statistic based information retrieval method. In the construction method of knowledge base, the common hypothesis is that the emergence of related term is the frequency of simultaneous emergence of a set of documents. Using the subject index file algorithms and the 'and' operator of boolean logic based on this hypothesis, this study builds the knowledge base. In this research experiment, a subject of knowledge base is education. Using the book of the Introduction to Education, two experimental knowledge base systems is constructed by the different indexing method. One system has constructed by controlled language indexing method, and another system has constructed by natural language indexing method. The performance of two knowledge base system is evaluated.

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HIV Knowledge and Attitude and Its Related Factors of Cambodian Adolescents (캄보디아 청소년의 HIV 지식 및 태도와 영향요인)

  • Pahn, Jihyon;Yang, Youngran;Lewis, Frances M.
    • Journal of Convergence for Information Technology
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    • v.10 no.8
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    • pp.108-119
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    • 2020
  • This describes the level of knowledge and attitudes about HIV and their related factors among Cambodian adolescents. A cross-sectional design was used to examine the knowledge and attitude of 463 Cambodian high school students using HIV-KQ-18 (HIV-Knowledge Questionnaire-18) and HIV/AIDS Behavior Surveillance Survey Index (measuring attitude about HIV). The majority of the adolescents had a relatively low level of overall HIV knowledge (6.70 ± 3.66 (range: 0-16)) and held a very negative attitude (1.92 ± 0.87 points (range: 0-4)) toward the disease. Using multiple regression analysis, being male (β = 0.28, p < 0.001) and using YouTube as a social network service (β = 0.33, p = 0.035) were found to be independent factors associated with higher level of HIV knowledge. Study findings suggest the importance of informing policymakers and school nurses about the need to develop a and require a culturally sensitive specific health education program on HIV for Cambodian adolescents.

The Definition of Data Structure for Design Knowledge Database and Development of the Interface Program for using Natural Language Processing (설계지식 데이터베이스의 자료구조 규명과 자연어처리를 이용한 인터페이스 프로그램 개발)

  • 이정재;이민호;윤성수
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.43 no.6
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    • pp.187-196
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    • 2001
  • In this study, by using the natural language processing of the field of artificial intelligence, automated index was performed. And then, the Natural Language Processing Interface for knowledge representation(NALPI) has been developed. Furthermore, the DEsign KnOwledge DataBase(DEKODB) has been also developed, which is designed to interlock the knowledge base. The DEKODB processes both the documented design-data, like a concrete standard specification, and the design knowledge from an expert. The DEKODB is also simulates the design space of structures accordance with the production rule, and thus it is determined that DEKODB can be used as a engine to retrieve new knowledge and to implement knowledge base that is necessary to the development of automatic design system. The application field of the system, which has been developed in this study, can be expanded by supplement of the design knowledge at DEKODB and developing dictionaries for foreign languages. Furthermore, the perfect automation at the data accumulation and development of the automatic rule generator should benefit the unified design automation.

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Using Balanced Scorecard to Explore Learning Performance of Enterprise Organization

  • Chiu, Chung-Ching;Tsai, Chih-Hung;Chung, Yi-Chan
    • International Journal of Quality Innovation
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    • v.8 no.1
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    • pp.40-75
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    • 2007
  • In the early industrial age which with high intensity of machine and labor, using financial measurement index was good enough to tie in company's mechanization and philosophy of management and been in efficiency. But being comply with "New Economic age," a new economic environment is full of knowledge and information, the enterprise competition had changed from tangible assets, plants to intangible innovation ability of knowledge. As recognizing the new tendency by enterprise, they value gradually the growth and influence from learning. Practice of organization learning not only needs firm structure and be in coordination with both hardware and software, but also needs an affect measurement model to offer enterprise to estimate learning performance. It's a good instrument of financial performance measure mold in the past years, But it's for measuring the past, couldn't formulate enterprise trend to future, hard to estimate investment for future, such as development of products, organization learning, knowledge management etc, as which intangible assets and knowledge ability just the key factors of being win around competition environment in the future. In 1992, Kaplan and Norton brought up Balance Scorecard (BSC) on Harvard Business Review, as an instrument helping enterprise to measure performance, which is being considered to be a most influence management instrument. It added non-financial index such as customer, internal process and learning growth besides traditional financial index, as offering enterprise an index to measure and manage intangible assets and intellectual property. As being aware of organization learning is hard to be ignored in the new economic age, this research is based on learning and growth of BSC, and citing one national material company try to let the most difficult measurement performance of organization learning, to be estimate through BSC, analyze of factor and individual case, to discuss the company how to make the related strategy and vision of organization learning to develop learning and growth of the structure of BSC, subject the matter of out put factors to be discussed, and measure the outcomes as a result of research. The research affect offers (1) the base implement procedure of carrying out BSC; (2) the reference of formulating measurement index while enterprise using BSC to estimate performance of organization learning; (3) the possibility bottleneck maybe forcing while carrying out BSC, to be an improvement or preventive for enterprise.

Quantitative Causal Reasoning in Stock Price Index Prediction Model

  • Kim, Myoung-Joon;Ingoo Han
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1998.10a
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    • pp.228-231
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    • 1998
  • Artificial Intelligence literatures have recognized that stock market is a highly unstructured and complex domain so that it is difficult to find knowledge that belongs to that domain. This paper demonstrates that the proposed QCOM can derive global knowledge about stock market on the basis of a set of local knowledge and express it as a digraph representation. In addition, inference mechanism using quantitative causal reasoning can describe the qualitative and quantitative effects of exogenous variables on stock market.

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