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Journal of Systems Integration

, Volume 6, Issue 3, pp 241–259 | Cite as

A predicate-driven document filing system

  • Zhijian Zhu
  • Qianhong Liu
  • James A. Mchugh
  • Peter A. Ng
Article

Abstract

This paper presents a predicate-driven document filing system for organizing and automatically filing documents. A document model consists of two basic elements: frame templates representing document classes, and folders which are repositories of frame instances. The frame templates can be organized to form a document type hierarchy, which helps classify and file documents. Frame instances are grouped into a folder on the basis of user-defined criteria, specified as predicates which determine whether a frame instance belongs to a folder. Folders can naturally organized into a folder organization which represents the user's real world document filing system. The predicate consistency problem is discussed to eliminate two abnormalities from a folder organization: inapplicable edges (filing paths) and redundant folders. An evaluating net (including an association dictionary, an instantiation component and a production system) is then proposed for evaluating whether a frame instance satisfies the predicate of a folder during document filing. And the concept of consistency a rule base is also discussed.

Keywords

Document modeling document filing predicate fact base and rule base 

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References

  1. 1.
    H. Adeli.Knowledge Engineering. McGraw-Hill, New York, 1990.Google Scholar
  2. 2.
    A. Celentano, M.G. Fugini, and S. Pozzi. Querying Office Systems about Document Roles. InProc. of the 14th Annual Int. ACM/SIGIR Conf. on Research and Development in Information Retrieval, pages 183–189, Chicago, Illinois, October 1991.Google Scholar
  3. 3.
    A. Celentano, M.G. Fugini, and S. Pozzi. Knowledge-Based Document Retrieval in Office Environments: The Kabiria System.ACM Transactions on Office Information Systems, 13(3):237–268, July 1995.Google Scholar
  4. 4.
    S. Christodoulakis, M. Theodoridou, F. Ho, M. Papa, and A. Pathria. Multimedia Document Presentation, Information Extraction, and Document Formation in MINOS: A Model and System.ACM Transactions on Office Information Systems, 4(4):345–383, October 1986.Google Scholar
  5. 5.
    W.F. Clocksin and C.S. Mellish.Programming in Prolog. Springer-Verlag, New York, 1981.Google Scholar
  6. 6.
    W.B. Croft and D. W. Stemple. Supporting Office Document Architectures with Constrained Types. InProc. of ACM SIGMOD International Conf. on Management of Data, pages 504–509, 1987.Google Scholar
  7. 7.
    P. Dadam and V. Linnemann. Advanced Information Management (AIM): Advanced Database Technology for Integrated Applications.IBM Systems Journal, 28(4):661–681, 1989.Google Scholar
  8. 8.
    S. Gibbs and D. Tsichritzis. A Data Modeling Approach for Office Information Systems.ACM Transactions on Office Information Systems, 1(4):299–319, October 1983.Google Scholar
  9. 9.
    X. Hao.Automatic Office Document Classification and Information Extraction. PhD Thesis, Department of Computer and Information Science, New Jersey Institute of Technology, Newark, New Jersey, August 1995.Google Scholar
  10. 10.
    X. Hao, J.T.L. Wang, M.P. Bieber, and P.A. Ng. Heuristic Classification of Office Documents.International Journal of Artificial Intelligence Tools, 3(2):233–265, 1994.Google Scholar
  11. 11.
    X. Hao, J.T.L. Wang, and P.A. Ng. Nested Segmentation: An Approach for Layout Analysis in Document Classification. InProc. of the Second International Conference on Document analysis and Recognition, pages 319–322, Tsukuba Science City, Japan, October 1993.Google Scholar
  12. 12.
    Q. Liu and P.A. Ng. A Browser of Supporting Vague Query Processing in an Office Document System.Journal of Systems Integration, 5(1):61–82, 1995.Google Scholar
  13. 13.
    Q. Liu and P.A. Ng. A Query Generalizer for Providing Cooperative Responses in an Office Document System (revised version). Submitted to Data and Knowledge Engineering Journal, October 1995.Google Scholar
  14. 14.
    Q. Liu and P.A. Ng.Document Processing and Retrieval: Text Processing. Kluwer Academic Publishers, 1996.Google Scholar
  15. 15.
    Q. Liu, J.T.L. Wang, and P.A. Ng. An Office Document Retrieval System with the Capability of Processing Incomplete and Vague Queries. InProc. of the Fifth Intl. Conf. on Software Engineering and Knowledge, pages 11–17, San Francisco, CA, June 1993.Google Scholar
  16. 16.
    Q. Liu, J.T.L. Wang, and P.A. Ng. On Research Issues Regarding Uncertain Query Processing In An Office Document Retrieval System.Journal of Systems Integration, 3(2):163–194, 1993.Google Scholar
  17. 17.
    F. Mhlanga, J.T.L. Wang, T.H. Shiau, and P.A. Ng. A Query Algebra for Office Documents. InProc. of the 2nd Intl. Conf. on Systems Integration, pages 458–467, Morristown, New Jersey, June 1992.Google Scholar
  18. 18.
    F. Mhlanga, Z. Zhu, J.T.L. Wang, and P.A. Ng. A New Approach to Modeling Personal Office Documents.Data and Knowledge Engineering, 17(2):127–158, November 1995.Google Scholar
  19. 19.
    S. Pozzi and A. Celentano. Knowledge-Based Document Filing.IEEE Expert, pages 34–45, October 1993.Google Scholar
  20. 20.
    F.Y. Shih, S. Chen, D.C.D. Hung, and P.A. Ng. A Document Segmentation, Classification and Recognition System. InProceedings of 2nd International Conference on Systems Integration, pages 258–267, Morristown, NJ, June 1992.Google Scholar
  21. 21.
    C. Thanos.Multimedia Office Filing: The MULTOS Approach. Elsevier Science Publishers B. V., 1990.Google Scholar
  22. 22.
    J.T.L. Wang, F.S. Mhlanga, Q. Liu, W.C. Shang, and P.A. Ng. An Intelligent Documentation Support Environment. InProc. of the Fifth International Conference on Software Engineering and Knowledge Engineering, pages 429–436, San Francisco, CA, June 1993.Google Scholar
  23. 23.
    J.T.L. Wang, F.S. Mhlanga, and P.A. Ng. A New Approach to Modeling Office Documents.ACM SIGOIS Bulletin, 14(2):46–55, December 1993.Google Scholar
  24. 24.
    J.T.L. Wang and P.A. Ng. TEXPROS: An Intelligent Document Processing System.International Journal of Software Engineering and Knowledge Engineering, 15(4):171–196, April 1992.Google Scholar
  25. 25.
    C. Wei, J.T.L. Wang, X. Hao, and P.A. Ng. In Deductive Learning and Knowledge Representation for Document Classification: The TEXPROS Approach. InProceedings of 3rd International Conference on Systems Integration, pages 1166–1175, Sao Paulo, SP, Brazil, August 1994.Google Scholar
  26. 26.
    Z. Zhu.Document Filing based upon Predicates. PhD Thesis proposal, Department of Computer and Information Science, New Jersey Institute of Technology, Newark, New Jersey, October 1994.Google Scholar
  27. 27.
    Z. Zhu, J.A. McHugh, J.T.L. Wang, and P.A. Ng. A Formal Approach to Modeling Office Information Systems.Journal of Systems Integration, 4(4):373–403, December 1994.Google Scholar

Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Zhijian Zhu
    • 1
  • Qianhong Liu
    • 1
  • James A. Mchugh
    • 1
  • Peter A. Ng
    • 1
  1. 1.Institute for Integrated Systems Research, Department of Computer and Information ScienceNew Jersey Institute of TechnologyNewark

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