Querying E-Catalogs Using Content Summaries

  • Aixin Sun
  • Boualem Benatallah
  • Mohand-Saïd Hacid
  • Mahbub Hassan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4275)


With the rapid development of e-services on the Web, increasing number of e-catalogs are becoming accessible to users. A large number of e-catalogs provide information about similar type of products/services. To simplify users information searching effort, data integration systems have being developed to integrate e-catalogs providing similar type of information such that users can query those e-catalogs with a mediator through an uniform query interface. The conventional approach to answer a query received by a mediator is to select e-catalogs purely based on their query capabilities, i.e., query interface specifications. However, an e-catalog having the capability to answer a query does not mean it has relevant answers to the query. To remedy the wasted resources of querying catalogs that do not generate an answer, in this paper, we propose to use catalog content summary as a filter and select the relevant e-catalogs to answer a given query based not only on their query capabilities but also on their content relevance to the query. A multi-attribute content (MAC) summary is proposed to describe an e-catalog with respect to its content. With MAC summary, an e-catalog is selected to answer a query only if the e-catalog is likely having answers to the query. MAC summary can be constructed and updated using answers returned from e-catalogs and therefore the e-catalogs need not be cooperative. We evaluated MAC summary on 50 e-catalogs, and the experimental results were promising.


Query Processing Range Query Content Summary User Query Query Plan 
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.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval, 1st edn. Addison-Wesley, Reading (1999)Google Scholar
  2. 2.
    Baina, K., Benatallah, B., Paik, H.-Y., Toumani, F., Rey, C., Rutkowska, A., Susanto, H.: WS-CatalogNet: An infrastructure for creating, peering, and querying e-catalog communities. In: Proc. of VLDB 2004, Toronto, Canada, August 2004, pp. 1325–1328 (2004)Google Scholar
  3. 3.
    Benatallah, B., Hacid, M.-S., Paik, H.-Y., Rey, C., Toumani, F.: Towards semantic-driven, flexible and scalable framework for peering and quering e-catalog communities. Information Systems 31(4), 266–294 (2006)CrossRefGoogle Scholar
  4. 4.
    Brin, S., Page, L.: The anatomy of a large-scale hypertextual web search engine. Computer Networks 30(1-7), 107–117 (1998)Google Scholar
  5. 5.
    Caverlee, J., Liu, L., Rocco, D.: Discovering and ranking web services with basil: a personalized approach with biased focus. In: Proc. of ICSOC 2004, pp. 153–162. ACM Press, New York (2004)Google Scholar
  6. 6.
    Chakrabarti, K., Chaudhuri, S., won Hwang, S.: Automatic categorization of query results. In: Proc. of ACM SIGMOD 2004, Paris, France, pp. 755–766. ACM Press, New York (2004)CrossRefGoogle Scholar
  7. 7.
    Cheng, X., Dong, G., Lau, T., Su, J.: Data integration by describing sources with constraint databases. In: Proc. of ICDE 1999, Sydney, Australia. IEEE Computer Society Press, Los Alamitos (1999)Google Scholar
  8. 8.
    Conrad, J.G., Claussen, J.R.S.: Early user—system interaction for database selection in massive domain-specific online environments. ACM Trans. Inf. Syst. 21(1), 94–131 (2003)CrossRefGoogle Scholar
  9. 9.
    Fan, J., Kambhampati, S.: A snapshot of public web services. SIGMOD Record 34(1), 24–32 (2005)CrossRefGoogle Scholar
  10. 10.
    Gelle, E., Faltings, B.: Solving mixed and conditional constraint satisfaction problems. Constraints 8(2), 107–141 (2003)MathSciNetMATHCrossRefGoogle Scholar
  11. 11.
    Halevy, A.Y.: Answering queries using views: A survey. VLDB Journal 10(4), 270–294 (2001)MATHCrossRefGoogle Scholar
  12. 12.
    Ibarra, O.H., Su, J.: On the containment and equivalence of database queries with linear constraints (extended abstract). In: Proc. of PODS 1997, Tucson, Arizona, pp. 32–43. ACM Press, New York (1997)CrossRefGoogle Scholar
  13. 13.
    Lee, D.H., Kim, M.H.: Database summarization using fuzzy isa hierarchies. IEEE Transactions on Systems, Man, and Cybernetics, Part B 27(1), 68–78 (1997)CrossRefGoogle Scholar
  14. 14.
    Levy, A.Y., Rajaraman, A., Ordille, J.J.: Querying heterogeneous information sources using source descriptions. In: Proc. of VLDB 1996, Bombay, India, pp. 251–262. Morgan Kaufmann, San Francisco (1996)Google Scholar
  15. 15.
    Liu, L.: Query routing in large-scale digital library systems. In: Proc. of ICDE 1999, Washington DC, pp. 154–163. IEEE Computer Society Press, Los Alamitos (1999)Google Scholar
  16. 16.
    McCann, R., AlShebli, B.K., Le, Q., Nguyen, H., Vu, L., Doan, A.: Mapping maintenance for data integration systems. In: Proc. of VLDB 2005, Trondheim, Norway (2005)Google Scholar
  17. 17.
    Millstein, T., Levy, A., Friedman, M.: Query containment for data integration systems. In: Proc. of PODS 2000, Dallas, Texas, pp. 67–75. ACM Press, New York (2000)CrossRefGoogle Scholar
  18. 18.
    Nie, Z., Kambhampati, S., Nambiar, U.: Effectively mining and using coverage and overlap statistics for data integration. IEEE Trans. on Knowledge and Data Eng. 17(5), 638–651 (2005)CrossRefGoogle Scholar
  19. 19.
    OCEAN. On-board Communication, Entertainment, And iNformation, Available at:
  20. 20.
    Powell, A.L., French, J.C.: Comparing the performance of collection selection algorithms. ACM Trans. Inf. Syst. 21(4), 412–456 (2003)CrossRefGoogle Scholar
  21. 21.
    Saint-Paul, R., Raschia, G., Mouaddib, N.: General purpose dataset summarization. In: Proc. of VLDB 2005, Trondheim, Norway (2005)Google Scholar
  22. 22.
    Ullman, J.D.: Information integration using logical views. In: Afrati, F.N., Kolaitis, P.G. (eds.) ICDT 1997. LNCS, vol. 1186, pp. 19–40. Springer, Heidelberg (1996)Google Scholar
  23. 23.
    Yu, C.T., Philip, G., Meng, W.: Distributed top-n query processing with possibly uncooperative local systems. In: Proc. of VLDB 2003, Berlin, Germany, September 2003, pp. 117–128. Morgan Kaufmann, San Francisco (2003)CrossRefGoogle Scholar
  24. 24.
    Zhang, C., Naughton, J., DeWitt, D., Luo, Q., Lohman, G.: On supporting containment queries in relational database management systems. SIGMOD Rec. 30(2), 425–436 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Aixin Sun
    • 1
  • Boualem Benatallah
    • 1
  • Mohand-Saïd Hacid
    • 2
  • Mahbub Hassan
    • 1
  1. 1.School of Computer Science and EngineeringUniversity of New South WalesSydneyAustralia
  2. 2.LIRIS – UFR d’InformatiqueUniversite Claude Bernard Lyon 1Villeurbanne cedexFrance

Personalised recommendations