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Annotation Based Query Answer over Inconsistent Database

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Abstract

In this paper, we introduce a concept of Annotation Based Query Answer, and a method for its computation, which can answer queries on relational databases that may violate a set of functional dependencies. In this approach, inconsistency is viewed as a property of data and described with annotations. To be more precise, every piece of data in a relation can have zero or more annotations with it and annotations are propagated along with queries from the source to the output. With annotations, inconsistent data in both input tables and query answers can be marked out but preserved, instead of being filtered in most previous work. Thus this approach can avoid information loss, a vital and common deficiency of most previous work in this area. To calculate query answers on an annotated database, we propose an algorithm to annotate the input tables, and redefine the five basic relational algebra operations (selection, projection, join, union and difference) so that annotations can be correctly propagated as the valid set of functional dependency changes during query processing. We also prove the soundness and completeness of the whole annotation computing system. Finally, we implement a prototype of our system, and give some performance experiments, which demonstrate that our approach is reasonable in running time, and excellent in information preserving.

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References

  1. Abiteboul S, Hull R, Vianu V. Foundations of Databases. Addison-Wesley, 1995.

  2. Arenas M, Bertossi L E, Chomicki J. Consistent query answers in inconsistent databases. In Proc. the 18th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Philadelphia, USA, May 31–June 2, 1999, pp.68–79.

  3. Bohannon P, Flaster M, Fan W, Rastogi R. A cost-based model and effective heuristic for repairing constraints by value modification. In Proc. the 2005 ACM SIGMOD Int. Conf. Management of Data, Baltimore, USA, June 14–16, 2005, pp.143–154.

  4. Bertossi L, Bravo L, Franconi E, Lopatenko A. Complexity and approximation of ¯xing numerical attributes in databases under integrity constraints. In Proc. the 10th Int. Symp. Database Programming Languages, Trondheim, Norway, Aug. 28-29, 2005, pp.262–278.

  5. Wijsen J. Database repairing using updates. ACM Transactions on Database Systems, 2005, 30(3): 722–768.

    Article  Google Scholar 

  6. Lopatenko A, Bravo L. E±cient approximation algorithms for repairing inconsistent databases. In Proc. the 23rd Int. Conf. Data Engineering, Istanbul, Turkey, Apr. 15-20, 2007, pp.216–225.

  7. Chomicki J, Marcinkowski J. Minimal change integrity maintenance using tuple deletions. Information and Computation, 2005, 197(1/2): 90–121.

    Article  MATH  MathSciNet  Google Scholar 

  8. Franconi E, Palma A L, Leone N, Perri S, Scarcello F. Census data repair: A challenging application of disjunctive logic programming. In Proc. the 8th Int. Conf. Logic for Programming, Artificial Intelligence, and Reasoning, Havana, Cuba, Dec. 3–7, 2001, pp.561–578.

  9. Bravo L, Bertossi L. Logic programs for consistently querying data integration systems. In Proc. the 18th International Joint Conference on Artificial Intelligence, Acapulco, Mexico, Aug. 9–15, 2003, pp.10–15.

  10. Chomicki J. Consistent query answering: Five easy pieces. In Proc. the 11th Int. Conf. Database Theory, Barcelona, Spain, Jan. 10–12, 2007, pp.1–17.

  11. Andritsos P, Fuxman A, Miller R J. Clean answers over dirty databases: A probabilistic approach. In Proc. the 22nd Int. Conf. Data Engineering, Atlanta, USA, Apr. 3–8, 2006, p.30.

  12. Zhang X, Chomicki J. On the semantics and evaluation of top-k queries in probabilistic databases. In Proc. the 24th International Conference on Data Engineering Workshops, Cancún, México, Apr. 7–12, 2008, pp.556–563.

  13. Cormode G, Li F, Yi K. Semantics of ranking queries for probabilistic data and expected ranks. In Proc. the 25th International Conference on Data Engineering, Shanghai, China, Mar. 29–Apr. 2, 2009, pp.305–316.

  14. Dalvi N, Suciu D. Efficient query evaluation on probabilistic databases. In Proc. the 30th International Conference on Very Large Data Bases, Toronto, Canada, Aug. 31–Sept. 3, 2004, pp.864–875.

  15. Hua M, Pei J, Zhang W, Lin X. Efficiently answering probabilistic threshold top-k queries on uncertain data. In Proc. the 24th International Conference on Data Engineering, Cancún, México, April 7–12, 2008, pp.1403–1405.

  16. Soliman M, Ilyas I, Chang K C. Top-k query processing in uncertain databases. In Proc. the 23rd International Conference on Data Engineering, Istanbul, Turkey, Apr. 15–20, 2007, pp.896–905.

  17. Klug A C. Calculating constraints on relational expressions. ACM Transactions on Database Systems, 1980, 5(3): 260–290.

    Article  MATH  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Fudan University, Shanghai, 200433, China

    Ai-Hua Wu, Zi-Jing Tan & Wei Wang (Senior Member, CCF)

  2. School of Computer Science, Shanghai Maritime University, Shanghai, 200135, China

    Ai-Hua Wu

Authors
  1. Ai-Hua Wu
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  2. Zi-Jing Tan
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  3. Wei Wang
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Corresponding author

Correspondence to Zi-Jing Tan.

Additional information

Supported by the National Natural Science Foundation of China under Grant No. 60603043, and the Program of Shanghai Municipal Education Commission under Grant No.06FZ030.

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Wu, AH., Tan, ZJ. & Wang, W. Annotation Based Query Answer over Inconsistent Database. J. Comput. Sci. Technol. 25, 469–481 (2010). https://doi.org/10.1007/s11390-010-9338-9

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  • DOI: https://doi.org/10.1007/s11390-010-9338-9

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