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Flexible Query Languages for Relational Databases: An Overview

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Flexible Databases Supporting Imprecision and Uncertainty

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 203))

Abstract

Managers rely more and more on the use of databases to obtain insights and updated information on activities of their institutions and companies. More and more people, from experts to non-experts, are depending on information from databases, to fulfill everyday tasks, notably those related to decision making. Basically, the content of a database describes selected aspects of the real world relevant for a given company, institution, etc. Often, our knowledge about the entities represented in a database as well as our preferences as to what should be retrieved from a database are imperfect or imprecise. This raises a question of a proper modeling of imperfect information in the context of database management systems (DBMSs).

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References

  1. Baldwin JF, Coyne MR, Martin TP (1993) Querying a database with fuzzy attribute values by iterative updating of the selection criteria. In: Proceedings of International Joint Conference on Artificial Intelligence (IJCAI’93)

    Google Scholar 

  2. Baldwin JF, Martin TP, Pilsworth BW (1995) FRIL - Fuzzy and evidential reasoning in artificial intelligence. John Wiley & Sons, Inc, New York

    Google Scholar 

  3. Bosc P (1999) Fuzzy Databases. In: Bezdek J, Dubois D, Prade H (eds) Fuzzy sets in approximate reasoning and information systems, The Handbooks of Fuzzy Sets Series. Kluwer Academic Publishers, pp 403–468

    Google Scholar 

  4. Bosc P, Lietard L, Pivert O (2000) About ill-known data and equi-join operations. In: Larsen HL, Kacprzyk J, Zadrozny S, Andreasen T, Christiansen H (eds) Flexible query answering systems. Recent advances. Physica-Verlag, Heidelberg New York, pp 65–74

    Google Scholar 

  5. Bosc P, Pivert O (1992) Fuzzy querying in conventional databases. In: Zadeh LA, Kacprzyk J (eds) Fuzzy logic for the management of uncertainty. John Wiley & Sons, pp 645–671

    Google Scholar 

  6. Bosc P, Pivert O (1993) An approach for a hierarchical aggregation of fuzzy predicates. In: Proceedings of 2nd IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’93), USA, pp 1231–1236

    Google Scholar 

  7. Bosc P, Pivert O (1995) SQLf: A relational database language for fuzzy querying. IEEE Transactions on Fuzzy Systems 3: 1–17

    Article  Google Scholar 

  8. Bosc P, Pivert O (1997) Fuzzy queries against regular and fuzzy databases. In: Andreasen T, Christiansen H, Larsen HL (eds) Flexible query answering systems. Kluwer Academic Publishers, pp 187–208

    Google Scholar 

  9. Bosc P, Pivert O (1997) On representation-based querying of databases containing ill-known values. In: Proceedings of International Symposium on Methodologies for Intelligent Systems (ISMIS’ 97), pp 477–486

    Google Scholar 

  10. Bosc P, Pivert O, Lietard L (2001) Aggregate operators in database flexible querying. In: Proceedings of 9th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’2001), Melbourne, Australia, pp 1231–1234

    Google Scholar 

  11. Bosc P, Pivert O, Lietard L (2003) On the comparison of aggregates over fuzzy sets. In: Bouchon-Meunier B, Foulloy L, Yager RR (eds) Intelligent systems for information processing. From representation to applications. Elsevier, pp 141–152

    Google Scholar 

  12. Buckles BP, Petry FE (1985) Query languages for fuzzy databases. In: Kacprzyk J, Yager RR (eds) Management decision support systems using fuzzy sets and possibility theory. Verlag, TUV Rheinland, pp 241–251

    Google Scholar 

  13. Buckles BP, Petry FE, Sachar HS (1986) Design of similarity-based relational databases. In: Prade H, Negoita CV (eds) Fuzzy logic in knowledge engineering. Verlag, TUV Rheinland, pp 3–7

    Google Scholar 

  14. Codd EF (1970) A relational model of data for large shared data banks. Communications of the ACM 13(6): 377–387

    Article  MATH  Google Scholar 

  15. Dubois D, Prade H (1990) Measuring properties of fuzzy sets: A general technique and its use in fuzzy query evaluation. Fuzzy Sets and Systems 38(2): 137–152

    Article  MATH  MathSciNet  Google Scholar 

  16. Dubois D, Prade H (1997) Using fuzzy sets in flexible querying: why and how?. In: Andreasen T, Christiansen H, Larsen HL (eds) Flexible query answering systems. Kluwer Academic Publishers, pp 45–60

    Google Scholar 

  17. Fodor J, Yager RR (2000) Fuzzy set-theoretic operators and quantifiers. In: Dubois D, Prade H (eds) Fundamentals of fuzzy sets. Kluwer Academic Publishers, 125–193

    Google Scholar 

  18. Galindo J; Medina JM; Aranda GMC (1999) Querying fuzzy relational databases through fuzzy domain calculus. International Journal of Intelligent Systems 14(4): 375–411

    Article  MATH  Google Scholar 

  19. Galindo J, Medina JM, Cubero JC, García MT (2000) Fuzzy quantifiers in fuzzy domain calculus. In: Proceedings of 8th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU’2000), Spain, pp 1697–1702

    Google Scholar 

  20. Galindo J, Medina JM, Pons O, Cubero JC (1998) A server for fuzzy SQL queries. In: Andreasen T, Christiansen H, Larsen HL (eds) Flexible query answering systems. LNAI: 1495, Springer, pp 164–174

    Google Scholar 

  21. Kacprzyk J, Zadrozny S (1995) FQUERY for Access: fuzzy querying for Windows-based DBMS. In: Bosc P, Kacprzyk J (eds) Fuzziness in database management systems. Physica-Verlag, Heidelberg, pp 415–433

    Google Scholar 

  22. Kacprzyk J, Zadrozny S (1997) Implementation of OWA operators in fuzzy querying for Microsoft Access. In: Yager RR, Kacprzyk J (eds) The ordered weighted averaging operators: theory and applications. Kluwer, Boston, pp 293–306

    Google Scholar 

  23. Kacprzyk J, Zadrozny S (1999) Fuzzy querying via WWW: implementational issues. In: Proceedings of 7th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE’1999), Seoul, Korea, pp 603–608

    Google Scholar 

  24. Kacprzyk J, Zadrozny S (2000) On a fuzzy querying and data mining interface. Kybernetika 36: 657–670

    Google Scholar 

  25. Kacprzyk J, Zadrozny S (2000) On combining intelligent querying and data mining using fuzzy logic concepts. In: Bordogna G, Pasi G (eds) Recent research issues on the management of fuzziness in databases. Physica-Verlag, Heidelberg New York, pp 67–81

    Google Scholar 

  26. Kacprzyk J, Zadrozny S, Ziolkowski A (1989) FQUERY III+: a human-consistent database querying system based on fuzzy logic with linguistic quantifiers. Information Systems 6: 443–453

    Article  Google Scholar 

  27. Kacprzyk J, Ziolkowski A (1986) Database queries with fuzzy linguistic quantifiers. IEEE Transactions on Systems, Man and Cybernetics SMC 16: 474–479

    Article  Google Scholar 

  28. Kerre EE, De Cock M (1999) Linguistic modifiers: an overview. In: Chen G, Ying M., Cai K-Y (eds) Fuzzy logic and soft computing. Kluwer Academic Publishers, pp 69–85

    Google Scholar 

  29. Klir GJ, Folger TA (1988) Fuzzy sets, uncertainty and information, Prentice-Hall.

    Google Scholar 

  30. Lacroix M, Lavency P (1987) Preferences: putting more knowledge into queries. In: Proceedings of 13rd International Conference on Very Large Databases (VLDB’ 87), Brighton (GB), pp 217–225

    Google Scholar 

  31. Liu Y, Kerre EE (1998) An overview of fuzzy quantifiers (I). Interpretations. Fuzzy Sets and Systems 95: 1–21

    Article  MATH  MathSciNet  Google Scholar 

  32. Medina JM, Pons O, Vila MA (1994) GEFRED: a generalized model of fuzzy relational databases. Information Sciences 76(1–2): 87–109

    Article  Google Scholar 

  33. Petry FE (1996) Fuzzy databases: principles and applications. Kluwer Academic Publishers

    Google Scholar 

  34. Prade H, Testemale C (1984) Generalizing database relational algebra for the treatment of incomplete or uncertain information and vague queries. Information Sciences 34: 115–143

    Article  MATH  MathSciNet  Google Scholar 

  35. Prade H, Testemale C (1987) Representation of soft constraints and fuzzy attribute values by means of possibility distributions in databases. In: Bezdek JC (ed) Analysis of fuzzy information, vol. II, CRC Press, pp 213–229

    Google Scholar 

  36. Raju KVSVN, Majumdar AK (1988) Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database systems. ACM Transactions on Database Systems 13: 129–166

    Article  Google Scholar 

  37. Ramakrishnan R, Gehrke J (2000) Database management systems, McGraw-Hill.

    Google Scholar 

  38. Ribeiro RA (1993) Application of support logic theory to fuzzy multiple attribute decision problems, University of Bristol, UK

    Google Scholar 

  39. Ribeiro RA, Moreira AM (1999) Intelligent query model for business characteristcs. In: Proceedings of IEEE/WSES/IMACS CSCC’99 Conference, Greece

    Google Scholar 

  40. Ribeiro RA, Moreira AM (2003) Fuzzy query interface for a business database. International Journal of Human Computer Studies 58(4): 363–391

    Article  Google Scholar 

  41. Schmucker KJ (1984) Fuzzy sets, natural language computations, and risk analysis, Computer Science Press

    Google Scholar 

  42. Shenoi S, Melton A (1989) Proximity relations in the fuzzy relational database model. Fuzzy Sets and Systems 31: 285–296

    Article  MATH  MathSciNet  Google Scholar 

  43. Shenoi S, Melton A, Fan LT (1990) An equivalence classes model of fuzzy relational databases. Fuzzy Sets and Systems 38: 153–170

    Article  MATH  MathSciNet  Google Scholar 

  44. Tahani V (1977) A conceptual framework for fuzzy query processing: a step toward very intelligent database systems. Information Processing and Management 13: 289–303

    Article  MATH  Google Scholar 

  45. Takahashi Y (1991) A fuzzy query language for relational databases. IEEE Transactions on Systems, Man and Cybernetics SMC 21: 1576–1579

    Article  Google Scholar 

  46. Takahashi Y (1995) A fuzzy query language for relational databases. In: Bosc P, Kacprzyk J (eds) Fuzziness in database management systems. Physica-Verlag, Heidelberg, pp 365–384

    Google Scholar 

  47. Ullman JD (1982) Principles of database systems, Computer Science Press.

    Google Scholar 

  48. Umano M (1982) FREEDOM-0: a fuzzy database system. In: Gupta M, Sanchez E (eds) Fuzzy information and decision processes. North-Holland, Amsterdam, pp 339–347

    Google Scholar 

  49. Umano M, Fukami S (1994) Fuzzy relational algebra for possibility-distribution-fuzzy relational model of fuzzy data. Journal of Intelligent Information Systems 3: 7–27

    Article  Google Scholar 

  50. Yager RR (1994) Interpreting linguistically quantified propositions. International Journal of Intelligent Systems 9: 541–569

    MATH  Google Scholar 

  51. Zadeh LA (1965) Fuzzy sets. Information and Control 8: 338–353

    Article  MATH  MathSciNet  Google Scholar 

  52. Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoning - II. Information Sciences, 8: 219–269

    Google Scholar 

  53. Zadeh LA (1978) PRUF -a meaning representation language for natural languages. International Journal of Man-Machine Studies 10: 395–460

    MATH  MathSciNet  Google Scholar 

  54. Zadeh LA (1983) A computational approach to fuzzy quantifiers in natural languages. Computational Mathematics Applications 9: 149–184

    Article  MATH  MathSciNet  Google Scholar 

  55. Zadrozny S, Kacprzyk J (1998) Implementing fuzzy querying via the Internet/WWW: Java applets, ActiveX controls and cookies. In: Andreasen T, Christiansen H, Larsen HL (eds) Flexible query answering systems. LNAI: 1495, Springer, Berlin Heidelberg, pp 382–392

    Chapter  Google Scholar 

  56. Zemankova-Leech M, Kandel A (1984) Fuzzy relational databases - A key to expert systems. Koln, Germany, TUV Rheinland.

    Google Scholar 

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Rosado, A., Ribeiro, R.A., Zadrozny, S., Kacprzyk, J. (2006). Flexible Query Languages for Relational Databases: An Overview. In: Bordogna, G., Psaila, G. (eds) Flexible Databases Supporting Imprecision and Uncertainty. Studies in Fuzziness and Soft Computing, vol 203. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33289-8_1

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  • DOI: https://doi.org/10.1007/3-540-33289-8_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33288-6

  • Online ISBN: 978-3-540-33289-3

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