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Cooperative Answering through Controlled Query Relaxation

Published: 01 September 1997 Publication History

Abstract

This article presents methods to guide and control heuristically the relaxation of deductive and relational database queries. These methods enable a database system to compose responses that align with user needs. Query relaxation provides a user with an automatic means to identify new queries that are related to the user's original query. However, for large databases, many relaxations might be possible. These methods to control and restrict the relaxation process add focus and make relaxation more efficient. User restrictions over the database domain are expressed as user constraints, which restrict relaxed queries. The author presents a set of heuristics, based on semantic query-optimization techniques, for controlling relaxation. She then describes how the methods interact to relax queries, process user constraints, and apply the heuristic rules. Finally, she shows how to use electronic thesaurii as sources of semantic information and gives examples of two thesaurus-based applications of user-constrained relaxation.

References

[1]
T. Gaasterland, Cooperative Answers for Database Queries, PhD thesis, Univ. of Maryland, Dept. of Computer Science, College Park, Md., 1992.
[2]
J. Minker and A. Gal, "Producing Cooperative Answers in Deductive Databases," in Logic and Logic Grammar for Language Processing, P. Saint-Dizier and S. Szpakowics, eds., Ellis Horwood, New York, 1990.
[3]
A. Motro, "Intensional Answers to Database Queries," IEEE Trans. Knowledge and Data Engineering, Vol. 6, No. 3, June 1994, pp. 444-454.
[4]
T. Gaasterland and J. Lobo, "Qualified Answers That Reflect User Needs and Preferences," Proc. Int'l Conf. Very Large Databases, Morgan Kaufmann, San Francisco, 1994.
[5]
T. Gaasterland P. Godfrey and J. Minker, "Relaxation as a Platform for Cooperative Answering," J. Intelligent Information Systems, 1992.
[6]
W. Chu Q. Chen and M. Merzbacher, "Cobase: A Cooperative Database System," in Nonstandard Queries and Nonstandard Answers, R. Demolombe and T. Imielinski, eds., Oxford Univ. Press, Oxford, UK, 1994.
[7]
F. Cuppens and R. Demolombe, "How to Recognize Interesting Topics to Provide Cooperative Answering," Information Systems, Vol. 14, No. 2, 1989, pp. 163-173.
[8]
M.E. Pollack, "Plans as Complex Mental Attitudes," in Intentions in Communication, M.E. Pollack, P.R. Cohen, and J. Morgan, eds., MIT Press, Cambridge, Mass., 1990, pp. 77-103.
[9]
C. Shum and R. Muntz, "Implicit Representation for Extensional Answers," Proc. Second Int'l Conf. Expert Database Systems, Benjamin Cummings, Reading, Mass., 1989, pp. 497-522.
[10]
U.S. Chakravarthy J. Grant and J. Minker, "Logic Based Approach to Semantic Query Optimization," ACM Trans. Database Systems, Vol. 5, No. 2, June, 1990, pp. 62-207.
[11]
J. Minker and A. Gal, "Producing Cooperative Answers in Deductive Databases," in Logic and Logic Grammar for Language Processing, P. Saint-Dizier and S. Szpakowics, eds., Ellis Horwood, New York, 1990.

Cited By

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  • (2024)ASQP-RL Demo: Learning Approximation Sets for Exploratory QueriesCompanion of the 2024 International Conference on Management of Data10.1145/3626246.3654741(452-455)Online publication date: 9-Jun-2024
  • (2018)Answers Partitioning and Lazy Joins for Efficient Query Relaxation and Application to Similarity SearchThe Semantic Web10.1007/978-3-319-93417-4_14(209-224)Online publication date: 3-Jun-2018
  • (2016)Location Aware Keyword Query Suggestion Based on Document ProximityIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2015.246539128:1(82-97)Online publication date: 1-Jan-2016
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Information & Contributors

Information

Published In

cover image IEEE Expert: Intelligent Systems and Their Applications
IEEE Expert: Intelligent Systems and Their Applications  Volume 12, Issue 5
September 1997
84 pages

Publisher

IEEE Educational Activities Department

United States

Publication History

Published: 01 September 1997

Author Tags

  1. cooperative control
  2. logic and deduction
  3. nonstandard query answering
  4. query relaxation
  5. user preferences.

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View all
  • (2024)ASQP-RL Demo: Learning Approximation Sets for Exploratory QueriesCompanion of the 2024 International Conference on Management of Data10.1145/3626246.3654741(452-455)Online publication date: 9-Jun-2024
  • (2018)Answers Partitioning and Lazy Joins for Efficient Query Relaxation and Application to Similarity SearchThe Semantic Web10.1007/978-3-319-93417-4_14(209-224)Online publication date: 3-Jun-2018
  • (2016)Location Aware Keyword Query Suggestion Based on Document ProximityIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2015.246539128:1(82-97)Online publication date: 1-Jan-2016
  • (2016)A holistic and principled approach for the empty-answer problemThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-016-0431-825:4(597-622)Online publication date: 1-Aug-2016
  • (2012)Work out the semantic web searchAdvances in Artificial Intelligence10.1155/2012/8678312012(3-3)Online publication date: 1-Jan-2012
  • (2012)Approximating query answering on RDF databasesWorld Wide Web10.1007/s11280-011-0131-715:1(89-114)Online publication date: 1-Jan-2012
  • (2012)Towards fuzzy query-relaxation for RDFProceedings of the 9th international conference on The Semantic Web: research and applications10.1007/978-3-642-30284-8_53(687-702)Online publication date: 27-May-2012
  • (2011)Cooperative query answering by abstract interpretationProceedings of the 37th international conference on Current trends in theory and practice of computer science10.5555/1946370.1946394(284-296)Online publication date: 22-Jan-2011
  • (2010)Search space reduction for an efficient handling of empty answers in database flexible queryingProceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I10.5555/1893893.1893956(532-543)Online publication date: 8-Sep-2010
  • (2010)A method based on query caching and predicate substitution for the treatment of failing database queriesProceedings of the 18th international conference on Case-Based Reasoning Research and Development10.1007/978-3-642-14274-1_32(436-450)Online publication date: 19-Jul-2010
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