Journal of Intelligent Information Systems

, Volume 1, Issue 3–4, pp 355–382 | Cite as

Neighborhood and associative query answering

  • Wesley W. Chu
  • Qiming Chen


Cooperative query answering extends the classical notion of query answering to provide neighborhood and associated information. Neighborhood query answering relaxes the query and its answer via abstract representations. To integrate the abstraction view with the subsumption (is-a) and composition (part-of) views of type hierarchy, the notion of type abstraction hierarchy is introduced. To evaluate and control query relaxation, a nearness measure mechanism is provided. Associative query answering provides information conceptually related to, but not explicitly asked by the query. As object association is context sensitive, a DB-Pattern-KB framework is developed that couples domain-specific knowledge and participating objects in localized problem domains via virtual database patterns. Associative query answering can then be accomplished through tracing the behavior dependencies among cooperating objects in those problem domains. Such a framework allows related databases and knowledge bases to be linked dynamically in various contexts yet be maintained relatively independent of each other. The proposed approach has been implemented in the cooperative database system tested, CoBase, at UCLA. Our experience reveals that the proposed techniques are effective for cooperative query answering.


cooperative query answering associative query answering type abstraction hierarchy query pattern DB-pattern-KB semantic distance 


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  1. Abiteboul S. and Bonner, A. (1991). Objects and views.ACM-SIGMOD'91, pp. 238–247.Google Scholar
  2. Ait-Kaci, H. (1986). Type Subsumption as a Model of Computation. In L. Kerschburg (Ed.),Expert Database Systems.Google Scholar
  3. Bancilhon, F. and Khoshafian, S. (1986). A calculus for complex objects.Proc. PODS'86.Google Scholar
  4. Banerjee, J. et. al., (1987). Data Model Issues for Object-Oriented Applications.ACM Transactions on Office Information Systems.Google Scholar
  5. Bosc, P. and Galibourg, M. (1989). Indexing Techniques for a Fuzzy Data Base.Information Systems, 14, 493–499.Google Scholar
  6. Chen, Q. and Gardarin, G. (1988). An Implementation Model for Reasoning with Complex Object.SIGMOD Rec., 17, 164–172.Google Scholar
  7. Chu, W.W. and Chen, Q. (1993). A Structured Approach for Cooperative Query Answering.IEEE Transactions on Knowledge and Data Engineering, to appear.Google Scholar
  8. Chu, W.W., Chen, Q., and Lee, R. (1991a). Cooperative Query Answering via Type Abstraction Hierarchy. In S.M. Deen (Ed.),Cooperating Knowledge Based Systems, 1990, (pp. 271–292). New York: Elsevier.Google Scholar
  9. Chu, W.W., Chen, Q., and Page, T. (1991b). Cobase: cooperative distributed databases.Proc. 6th Brazilian Symp. Databases, (pp. 27–36). Brazil.Google Scholar
  10. Chu, W.W., Hwang, A., Lee, R., Chen, Q., Merzbacher, M., and Hecht, H. (1990). Fault tolerant distributed database system via data inference.Proc. 9th Symp. Reliable Distributed Systems, (pp. 86–94).Google Scholar
  11. Cuppens, F. and Demolombe, R. (1989a). Cooperative answering: a methodology to provide intelligent access to databases.Proc. 2nd Int. Conf. Expert Database Systems, (pp. 621–642).Google Scholar
  12. Cuppens, F. and Dmolombe, R. (1989b). How to Recognize Interesting Topics to Provide Cooperative Answering.Information Systems, 14, 163–173.Google Scholar
  13. Cuppens, F. and Demolombe, R. (1991). Extending Answers to Neighbor Entities in a Cooperative Answering Context.Decision Support Systems, 7, 1–11.Google Scholar
  14. Gal, A. and Minker, J. (1988). Informative and Cooperative Answers in Deductive Databases Using Integrity Constraints. InNatural Language Understanding and Logic Programming, (pp. 277–300). Amsterdam: North-Holland.Google Scholar
  15. Gaasterland, T., Godfrey, P., and Minker, J. (1991). Relaxation as a platform of cooperative answering.First Int. Workshop on Nonstandard Queries and Answers, 2, (pp. 101–120). Toulouse, France.Google Scholar
  16. Helm, R., Holland, J., and Gangopadhyay, D. (1990). Contracts: specifying behavioral compositions in object-oriented systems.Proc. OOPSLA'90, (pp. 169–179).Google Scholar
  17. Hemerly, A., Casanova, M. and Furtado, A. (1991). Cooperative Behavior through Request Modification. Working Paper, IBM Brasil, May.Google Scholar
  18. Kaplan, S.J. (1982). Cooperative Responses from a Portable Natural Language Query System.Artificial Intelligence, 19(2), 165–187.Google Scholar
  19. Kim, W. (1989). A model of queries for object-oriented databases.Proc. VLDB'89, (pp. 423–432).Google Scholar
  20. MacGregor, R. (1988). A deductive pattern matcher.Proc. AAAI'88, (pp. 403–408).Google Scholar
  21. Madsen, O. and Moller-Pedersen, B. (1989). Virtual classes: a powerful mechanism in object-oriented programming.Proc. OOPSLA'89, (pp. 397–406).Google Scholar
  22. Motro, A. (1990). FLEX: A Tolerant and Cooperative User Interface to Databases.IEEE Transactions on Knowledge and Data Engineering, 2, 231–246.Google Scholar
  23. Su, S. (1983). SAM*: A Semantic Association Model for Corporate and Scientific-Statistical Databases.Information Sciences, 29, 151–199.Google Scholar
  24. Webber, B.L. and Mays E. (1983). Varieties of user misconceptions: detection and correlation.Proc. 8th Int. Joint Conference on Artificial Intelligence, (pp. 650–652).Google Scholar
  25. Wiederhold, G., Mediators in the Architecture of Future Information Systems.IEEE COMPUTER, March, 38–49.Google Scholar
  26. Zadeh, L. (1965). Fuzzy Sets.Information and Control, 8, 338–353.Google Scholar

Copyright information

© Kluwer Academic Publishers 1992

Authors and Affiliations

  • Wesley W. Chu
    • 1
  • Qiming Chen
    • 1
  1. 1.Department of Computer ScienceUniversity of CaliforniaLos Angeles

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