Taxonomy Alignment for Interoperability Between Heterogeneous Digital Libraries

  • Jason J. Jung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4312)


Resources located in digital libraries are labeled (or classified) based on taxonomies. On multiple digital libraries, however, heterogeneity between taxonomies is a serious problem for efficient interoperation processes (e.g., information sharing and query transformation). In order to overcome this problem, we propose a novel framework based on aligning taxonomies of digital libraries. Thereby, the best mapping between concepts has to be discovered to maximize the summation of a set of partial similarities. For experimentation, three digital libraries were built based on different taxonomies. Taxonomy alignment-based resource retrieval was evaluated by human experts, and we measured recall and precision measures retrieved by concept replacement strategy.


Digital Library Query Expansion Class Similarity Alignment Process Conceptual Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Qiu, Y., Frei, H.P.: Concept based query expansion. In: Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval (SIGIR 1993), pp. 160–169. ACM Press, New York (1993)CrossRefGoogle Scholar
  2. 2.
    Menczer, F.: Lexical and semantic clustering by web links. Journal of the American Society for Information Science and Technology 55(14), 1261–1269 (2004)CrossRefGoogle Scholar
  3. 3.
    Jung, J.J.: Collaborative web browsing based on semantic extraction of user interests with bookmarks. Journal of Universal Computer Science 11(2), 213–228 (2005)Google Scholar
  4. 4.
    Euzenat, J., Valtchev, P.: Similarity-based ontology alignment in OWL-Lite. In: de Mántaras, R.L., Saitta, L. (eds.) Proc. of the 16th European Conference on Artificial Intelligence (ECAI 2004), Valencia, Spain, August 22-27, 2004, pp. 333–337. IOS Press, Amsterdam (2004)Google Scholar
  5. 5.
    Levenshtein, I.: Binary codes capable of correcting deletions, insertions, and reversals. Cybernetics and Control Theory 10(8), 707–710 (1996)MathSciNetGoogle Scholar
  6. 6.
    Euzenat, J.: An API for ontology alignment. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 698–712. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Welty, C.A., Guarino, N.: Supporting ontological analysis of taxonomic relationships. Data & Knowledge Engineering 39(1), 51–74 (2001)MATHCrossRefGoogle Scholar
  8. 8.
    Melnik, S., Garcia-Molina, H., Rahm, E.: Similarity flooding: A versatile graph matching algorithm and its application to schema matching. In: Proceedings of the 18th International Conference on Data Engineering (ICDE), pp. 117–128. IEEE Computer Society Press, Los Alamitos (2002)CrossRefGoogle Scholar
  9. 9.
    Cui, H., Wen, J.R., Nie, J.Y., Ma, W.Y.: Probabilistic query expansion using query logs. In: Proceedings of the 11th international conference on World Wide Web, pp. 325–332. ACM Press, New York (2002)CrossRefGoogle Scholar
  10. 10.
    Nie, J.Y.: Query expansion and query translation as logical inference. Journal of the American Society for Information Science and Technology 54(4), 335–346 (2003)CrossRefGoogle Scholar
  11. 11.
    Liu, Z., Chu, W.W.: Knowledge-based query expansion to support scenario-specific retrieval of medical free text. In: Proceedings of the 2005 ACM symposium on Applied computing (SAC 2005), pp. 1076–1083. ACM Press, New York (2005)Google Scholar
  12. 12.
    Zazo, Á.F., Figuerola, C.G., Berrocal, J.L.A., Rodríguez, E.: Reformulation of queries using similarity thesauri. Information Processing and Management: an International Journal 41(5), 1163–1173 (2005)CrossRefGoogle Scholar
  13. 13.
    Avesani, P., Giunchiglia, F., Yatskevich, M.: A large scale taxonomy mapping evaluation. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 67–81. Springer, Heidelberg (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jason J. Jung
    • 1
    • 2
  1. 1.Department of Computer & Information Eng.Inha UniversityIncheonKorea
  2. 2.INRIA Rhône-AlpesSaint Ismier cedexFrance

Personalised recommendations