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Formal Concept Analysis for Domain-Specific Document Retrieval Systems

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2256))

Abstract

Domain-specific information retrieval normally depends on general search engines, or systems which support browsing using handcrafted organisation of documents, but such systems are costly to build and maintain. An alternative approach for specialised domains is to build a retrieval system incrementally and dynamically by allowing users to evolve their own organisation of documents and to assist them in ensuring improvement of the system’s performance as it evolves. This paper describes a browsing mechanism for such a system based on the concept lattice of Formal Concept Analysis (FCA) in cooperation with incremental knowledge acquisition mechanisms. Our experience with a prototype suggests that a browsing scheme for a specific domain can be able to be collaboratively created and maintained by multiple users over time. It also appears that the concept lattice of FCA is a useful way of supporting the flexible open management of documents required by individuals, small communities or in specialised domains.

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References

  1. Aussenac-Gilles, N., Biebow B. and Szulman S. Revisiting Ontology Design: A Methodology Based on Corpus Analysis, 12 th European Conference on Knowledge Acquisition and Knowledge Management (EKAW 2000), Springer, 172–188, 2000.

    Google Scholar 

  2. Benjamins, V. R., Fensel, D., Decker, S. and Perez, A. G. (KA)2: building ontologies for the Internet: a mid-term report. International journal of human computer studies, Vol. 51, No. 3, 687–712, 1999.

    Article  Google Scholar 

  3. Carpineto, C. and Romano, G. GALOIS: An Order-Theoretic Approach to Conceptual Clustering, In Proceedings of the Machine Learning Conference, 33–40, 1993.

    Google Scholar 

  4. Carpineto, C. and Romano, G. Information retrieval through hybrid navigation of lattice representations. International Journal of Human-Computer Studies, 45, 553–578, 1996.

    Article  Google Scholar 

  5. Carpineto, C. and Romano, G. A Lattice Conceptual Clustering System and Its Application to Browsing Retrieval. Machine Learning, 24(2), 95–122, 1996.

    Google Scholar 

  6. Compton, P. and Jansen, R. A Philosophical Basis for Knowledge Acquisition. Knowledge Acquisition 2:242–257, 1990.

    Article  Google Scholar 

  7. Furnas, G. W., Landauer, T. K., Gomez, L. M. and Dumais, S. T. Statistical semantics: analysis of the potential performance of key-word information systems, Bell System Technical Journal, 62, 1753–1806, 1983.

    Google Scholar 

  8. Gaines, B. and Shaw, M. Cognitive and Logical Foundation of Knowledge Acquisition. The 5th Knowledge Acquisition for Knowledge Based Systems Workshop, 9.1–9.25, 1990.

    Google Scholar 

  9. Ganter, B. Computing with Conceptual Structures, Proceedings of the 8th International Conference on Conceptual Structure (ICCS 2000), Darmstadt, Springer, 453–467, 2000.

    Google Scholar 

  10. Ganter, B. and Wille, R. Conceptual Scaling, In: F. Roberts (ed.): Application of Combinatorics and Graph Theory to the Biological and Social Sciences, Springer, 139–167, 1989.

    Google Scholar 

  11. Ganter, B. and Wille, R. Formal Concept Analysis: mathematical foundations. Springer, Heidelberg, 1999.

    MATH  Google Scholar 

  12. Godin, R., Missaoui, R. and Alaoui, H. Learning algorithms using a Galois lattice structure, Proceedings of the Third International Conference on Tools for Artificial Intelligence, San Jose, CA: IEEE Computer Society Press, 22–29, 1991.

    Google Scholar 

  13. Godin, R., Missaoui, R. and Alaoui, H. Incremental concept formulation algorithms based on Galois (concept) lattices. Computational Intelligence, 11(2), 246–267, 1995.

    Article  Google Scholar 

  14. Kang, B. H., Yoshida, K., Motoda, H. and Compton, P. Help Desk System with Intelligent Interface, Applied Artificial Intelligence, 11: 611–631, 1997.

    Article  Google Scholar 

  15. Kim, M., Compton, P. and Kang, B. H. Incremental Development of a Web Based Help Desk System, Proceedings of the 4th Australian Knowledge Acquisition Workshop (AKAW99), University of NSW, Sydney, 13–29, 1999.

    Google Scholar 

  16. Lin, X. Map Displays for Information Retrieval, Journal of the American Society of Information Science, 48:40–54, 1997.

    Article  Google Scholar 

  17. Maedche, A. and Staab, S. Mining Ontologies from Text, 12 th European Conference on Knowledge Acquisition and Knowledge Management (EKAW), Springer, 189–202, 2000.

    Google Scholar 

  18. Marchionini, G. and Shneiderman, B. Finding facts vs. browsing knowledge in hypertext systems, IEEE Computer, 21, 70–80, 1988.

    Google Scholar 

  19. Priss, U. Faceted Information Representation, In: Stumme, Gerd (ed.), working with Conceptual Structures. Proceedings of the 8th International Conference on Conceptual Structures, Shaker Verlag, Achene, 84–94, 2000.

    Google Scholar 

  20. Richards, D. and Compton, P. Knowledge acquisition first, modelling later, Knowledge Acquisition, Modeling and Management, E. Plaza and R. Benjamins, Berlin, Springer: 237–252, 1997.

    Chapter  Google Scholar 

  21. Stumme, G. Hierarchies of Conceptual Scales. 12 th Banff Knowledge Acquisition, Modelling and Management, Eds. B Gaines; R Kremer; M Musen, Banff Canada, 16–21 Oct., SRDG Publication, University of Calgary, 1999.

    Google Scholar 

  22. Wille, R. Restructuring lattice theory: an approach based on hierarchies of concepts. In: Ivan Rival (ed.), Ordered sets, Reidel, Dordrecht-Boston, 445–470, 1982.

    Google Scholar 

  23. Wille, R. Concept lattices and conceptual knowledge systems. Computers and Mathematics with Applications, 23, 493–515, 1992.

    Article  MATH  Google Scholar 

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Kim, M., Compton, P. (2001). Formal Concept Analysis for Domain-Specific Document Retrieval Systems. In: Stumptner, M., Corbett, D., Brooks, M. (eds) AI 2001: Advances in Artificial Intelligence. AI 2001. Lecture Notes in Computer Science(), vol 2256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45656-2_21

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  • DOI: https://doi.org/10.1007/3-540-45656-2_21

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42960-9

  • Online ISBN: 978-3-540-45656-8

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