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경영정보학연구 = The journal of MIS research v.16 no.4, 2006년, pp.203 - 215  
본 등재정보는 저널의 등재정보를 참고하여 보여주는 베타서비스로 정확한 논문의 등재여부는 등재기관에 확인하시기 바랍니다.

개념 네트워크를 이용한 정보 검색 방법
Document Retrieval using Concept Network

허원창   (인하대학교 경영학부UU0001092  ); 이상진   (삼성네트웍스 기술솔루션사업팀CC0102087  );
  • 초록

    The advent of KM(knowledge management) concept have led many organizations to seek an effective way to make use of their knowledge. But the absence of right tools for systematic handling of unstructured information makes it difficult to automatically retrieve and share relevant information that exactly meet user's needs. we propose a systematic method to enable content-based information retrieval from corpus of unstructured documents. In our method, a document is represented by using several key terms which are automatically selected based on their quantitative relevancy to the document. Basically, the relevancy is calculated by using a traditional TFIDF measure that are widely accepted in the related research, but to improve effectiveness of the measure, we exploited 'concept network' that represents term-term relationships. In particular, in constructing the concept network, we have also considered relative position of terms occurring in a document. A prototype system for experiment has been implemented. The experiment result shows that our approach can have higher performance over the conventional TFIDF method.


  • 주제어

    Document Management .   Information Retrieval .   Concept Network .   Knowledge Management.  

  • 참고문헌 (22)

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    2. Fraeks. W. and Baeza-Yates, R., Information Retrieval: Data Structures and Algorithms, Prentice-Hall, 1992 
    3. Gopal, B. and Manber, U., Integrating Content-Based Access Mechanisms with Hierarchical File Systems, In ACM OSDI, pp. 265-278, 1999 
    4. Kim, Y. H. et al., "InfoFlow: A Web- based Workflow Management System," Proceedings of International Conference CALS/ EC Korea'99, 1999 
    5. Singhal, A., Salton, G., Mitra, M., and Buckley, C. "Document length normalization," Information Processing and Management, Vol. 32, No. 5, pp 619-633, 1996 
    6. Tiwana, A., "Knowledge Management Toolkit: Orchestrating IT, Strategy, and Knowledge Plafrom," Prentice Hall, Upper Saddle River, NJ 07458, 2002 
    7. Gudivada, V.N. and Raghavan, V.V., Design and evaluation of algorithms for image retrieval by spatial similarity, ACM Transaction on Information Systems, Vol. 13, No. 2, April, pp. 115-144, 1995 
    8. Grossman, D.A. and Frieder, O., "Information Retrieval: Algorithms and Heuristics," Kluwer Academic Publishers, 1998 
    9. Combarro, E.F., Montanes, E., Diaz, I., Ranilla, J, and Mones, R., "Introducing a Family of Linear Measures for Feature Selection in Text Categorization," IEEE Transaction on Knowledge and Data Engineering, Vol. 17, No. 9, 2005 
    10. Lewis, D.D., "Representation and Learning in Information Retrieval," University of Massachusetts, 1992 
    11. Kalt, T., "A New Probabilistic Model of Text Classification and Retrieval", University of Massachusetts, 1996 
    12. Chen, S.M., Wang, J.Y., "Fuzzy Query Processing for Document Retrieval Based on Extended Fuzzy Concept Network," Transactions on Systems, Man, and Cybernetics, Vol. 29, No. 1, February 1999 
    13. Gudivada, V. N., Reaghavan, V. V., Grosky, W. I., and Kasanagottu, R., "Information Retrieval On The World Wide Web," IEEE Internet Computing, September. October 1997 
    14. Sebastiani, F., "Machine Learning in Automated Text Categorization," ACM Computing Surveys, Vol. 34, No. 1, pp. 1-47, Mar. 2002 
    15. Awad, E.M. and Ghaziri, H. M., Knowledge Management, Prentice Hall, Upper Saddle River, NJ 07458, 2004 
    16. Chen, H., "Machine Learning for Information Retrieval: Neural Networks, Symbolic Learning, and Genetic Algorithms," MIS Department, College of Business and Public Administration, University of Arizona, July 1994 
    17. Faloutsos, C., Orad, D., "A Survey of Information Retrieval and Filtering Methods," University of Maryland, College Park, MD20742, 1994 
    18. Brin, S. and Page, L., "The anatomy of a large-scale hypertextual Web search engine," Proceedings of the seventh international conference on World Wide Web 7, pp. 107-117, 1998 
    19. Bartell, B.T. et al., "Optimizing Parameters in a Ranked Retrieval System Using Multi-Query Relevance Feedback," In the Proceeding of 3rd Annual Symposium on Document Analysis and Information Retrieval, 1992 
    20. Luhn, H., Keyword in Context Index for Technical Literature, American Documentation, XI (4), 1960 
    21. Zimmermann, H. J., Fuzzy Set Theory - and Its Applications, Kluwer Academic Publishers, 1991 
    22. Miller, G. A., Beckwith, R., "Introduction to Word-Net: An On-line Lexical Database," Princeton University,1993 

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