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QQL: A DB&IR Query Language

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Abstract

Traditional database query languages are based on set theory and crisp first order logic. However, many applications require retrieval-like queries which return result objects associated with a degree of being relevant to the query. Historically, retrieval systems estimate relevance by exploiting hidden object semantics whereas query processing in database systems relies on matching select-conditions with attribute values. Thus, different mechanisms were developed for database and information retrieval systems. In consequence, there is a lack of support for queries involving both retrieval and database search terms. In this work, we introduce the quantum query language (QQL). Its underlying unifying theory is based on the mathematical formalism of quantum mechanics and quantum logic. Van Rijsbergen already discussed the strong relation between the formalism of quantum mechanics and information retrieval. In this work, we interrelate concepts from database query processing to concepts from quantum mechanics and logic. As result, we obtain a common theory which allows us to incorporate seamlessly retrieval search into traditional database query processing.

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References

  1. Codd, E.F.: A database sublanguage founded on the relational calculus. In: ACM SIGFIDET Workshop on Data Description, Access and Control, pp. 35–61 (1971)

  2. Maier D. (1983). The Theory of Relational Databases. Computer Science Press, Rockville

    MATH  Google Scholar 

  3. Date C.J. and Darwen H. (1997). A Guide to the SQL Standard, 4th edn. Addison-Wesley, Reading

    Google Scholar 

  4. Baeza-Yates R. and Ribeiro-Neto B. (1999). Modern Information Retrieval. ACM Press, Essex

    Google Scholar 

  5. van Rijsbergen C.J. (1979). Information Retrieval. Butterworths, London

    Google Scholar 

  6. van Rijsbergen C.J. (2004). The Geometry of Information Retrieval. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  7. Dirac P. (1958). The Principles of Quantum Mechanics, 4th edn. Oxford University Press, Oxford

    MATH  Google Scholar 

  8. Gleason A. (1957). Measures on the Closed Subspaces of a Hilbert Space. J. Math. Mech. 6: 885–893

    MATH  MathSciNet  Google Scholar 

  9. Ziegler, M.: Quantum Logic: Order Structures in Quantum Mechanics. Technical report, University Paderborn, Germany (2005)

  10. von Neumann J. (1932). Grundlagen der Quantenmechanik. Springer, Berlin

    MATH  Google Scholar 

  11. Greechie, R. J.: On generating distributive sublattices of orthomodular lattices. In: Proceedings of the American Mathematical Society, vol. 67, No. 1, pp. 17–22 (1977)

  12. Marlow, A.R.: Orthomodular structures and physical theory. In: Mathematical Foundations of Qantum Theory. Academic Press, New York (1977)

  13. Zadeh L.A. (1988). Fuzzy Logic. IEEE Computer 21: 83–93

    Google Scholar 

  14. Schmitt, I.: Quantum query processing: unifying database querying and information retrieval. Technical report, Fakultät für Informatik, Univ. Magdeburg (2006)

  15. Fagin, R.: Fuzzy queries in multimedia database systems. In: Proceedings of the Seventeenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1–3, June 1998, Seattle, Washington, pp. 1–10. ACM Press, New York (1998)

  16. Ciaccia, P., Montesi, D., Penzo, W., Trombetta, A.: Imprecision and user preferences in multimedia queries: A generic algebraic approach. In: Schewe, K.D., Thalheim, B. (eds.) FoIKS: Foundations of Information and Knowledge Systems, First International Symposium, FoIKS 2000, Burg, Germany. February 14–17, 2000, vol. 1762. of Lecture Notes in Computer Science, Springer, Heidelberg, pp. 50–71 (2000)

  17. Schmitt, I., Schulz, N.: Similarity relational calculus and its reduction to a similarity algebra. In: Seipel, D., Turull-Torres J.M. (eds.) Third International Symposium on Foundations of Information and Knowledge Systems (FoIKS’04), Austria, February 17–20, Lecture Notes in Computer Science, vol. 2942, pp. 252–272. Springer, Berlin (2004)

  18. Schmitt, I., Schulz, N., Herstel, T.: WS-QBE: a QBE-like query language for complex multimedia queries. In: Chen, Y.P.P. (ed.) Proceedings of the 11th International Multimedia Modelling Conference (MMM’05), Melbourne, Australia, January 12–14, 2005, pp. 222–229. IEEE Computer Society Press, Los Alamitos (2005)

  19. Bellman R. and Giertz M. (1973). On the analytic formalism of the theory of fuzzy sets. Inform. Sci. 5: 149–156

    Article  MathSciNet  Google Scholar 

  20. Galindo, J., Urrutia, A., Piattini, M.: Fuzzy Databases: Modeling, Design and Implementation. Idea Group Publishing (2005)

  21. Bolloju, N.: A Calculus for Fuzzy Queries on Fuzzy Entity-Relationship Model. Technical Report 94/26, Department of Information Systems at the City Polytechnic of Hong Kong (1994)

  22. Galindo, J., Medina, J.M., Pons, O., Cubero, J.C.: A Server for Fuzzy SQL Queries. In: Andreasen, T., Christiansen, H., Larsen, H.L. (eds.) Flexible Query Answering Systems, Third International Conference, FQAS’98, Roskilde, Denmark, May 13–15, vol. 1495, pp. 164–174. Lecture Notes in Computer Science, Springer, Heidelberg (1998)

  23. Bosc P. and Pivert O. (1995). SQLf: A relational database language for fuzzy querying. IEEE Trans. Fuzzy Syst. 3: 1–17

    Article  Google Scholar 

  24. Takahashi Y. (1993). Fuzzy database query languages and their relational completeness theorem. IEEE Trans. Knowl. Data Eng. 5: 122–125

    Article  Google Scholar 

  25. Schulz, N., Schmitt, I.: A Survey of Weighted Scoring Rules in Multimedia Database Systems. Fakultät für Informatik, Universität Magdeburg (2002) (preprint 7)

  26. Fuhr N. and Rölleke T. (1997). A probabilistic relational algebra for the integration of information retrieval and databases systems. ACM Trans. Inform. Syst. (TOIS) 15: 32–66

    Article  Google Scholar 

  27. de Vries, A., Wilschut, A.: On the integration of IR and databases. In: Proceedings of the International Conference on Database Semantics (DS-8), Rotorua, New Zealand. pp. 16–31 (1999)

  28. de Vries, A., Blanken, H.: The relationship between IR and multimedia databases. In: Proceedings of the 20th IRSG colloqium: discovering new worlds of IR, Grenoble, France (1998)

  29. Gruska J. (1999). Quantum Computing. McGraw-Hill, New York

    Google Scholar 

  30. Chuang I., Nielsen M.A. and Chuang I.L. (2000). Quantum Computation and Quantum Information. Cambridge University Press, Cambridge

    MATH  Google Scholar 

  31. Rieffel E. and Polak W. (2000). An introduction to quantum computing for non-physicists. ACM Comput. Surv. 32: 330–335

    Article  Google Scholar 

  32. Beltrametti, E., van Fraassen, B. (eds.): (1981). Current Issues in Quantum Logic. Plenum Press, New York

    MATH  Google Scholar 

  33. Lock P. (1985). Connections among quantum logics, part 1: Quantum propositional logics. Int. J. Theor. Phys. 24: 43–53

    Article  MATH  MathSciNet  Google Scholar 

  34. Lock P. (1985). Connections among quantum logics, part 2: Quantum event logics. Int. J. Theor. Phys. 24: 55–61

    Article  MATH  MathSciNet  Google Scholar 

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Schmitt, I. QQL: A DB&IR Query Language. The VLDB Journal 17, 39–56 (2008). https://doi.org/10.1007/s00778-007-0070-1

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  • DOI: https://doi.org/10.1007/s00778-007-0070-1

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