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A Method to Induce Indicative Functional Dependencies for Relational Data Model

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Advances in Intelligent Informatics

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 320))

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Abstract

Relational model is one of the extensively used database models. However, with the contemporary technologies, high dimensional data which may be structured or unstructured are required to be analyzed for knowledge interpretation. One of the significant aspects of analysis is exploring the relationships existing between the attributes of large dimensional data. In relational model, the integrity constraints in accordance with the relationships are captured by functional dependencies. Processing of high dimensional data to understand all the functional dependencies is computationally expensive. More specifically, functional dependencies of the most prominent attributes will be of significant use and can reduce the search space of functional dependencies to be searched for. In this paper we propose a regression model to find the most prominent attributes of a given relation. Functional dependencies of these prominent attributes are discovered which are indicative and lead to faster results in decreased amount of time.

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References

  1. Synthesizing Third Normal Form Relations from Functional Dependencies philip a. bernstein, University of Toronto. ACM Transactions on Database Systems 1(4) (December 1976)

    Google Scholar 

  2. Yao, H., Hamilton, H.J., Butz, C.: FDMine Discovering Functional Dependencies in a Database Using Equivalences. In: International Conference on Data Mining 2002, pp. 729–732 (2002)

    Google Scholar 

  3. Mannila, H., Raiha, K.-J.: On the complexity of inferring functional dependencies. Discrete Applied Mathematics 40, 237–243 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  4. Bra, P.D., Paredaens, J.: Horizontal decompositions for handling exceptions to functional dependencies. In: Gallaire, H., Minker, J., Nicolas, J.M. (eds.) Advances in Database Theory, vol. 2, pp. 123–141. Plenum Publishing Company, New York (1984)

    Google Scholar 

  5. Huhtala, Y., Krkkinen, J., Porkka, P., Toivonen, H.: TANE: An Efficient Algorithm for Discovering Functional and Approximate Dependencies. The Computing Journal 42(2), 100–111 (1999)

    Article  MATH  Google Scholar 

  6. Flach, P.A., Savnik, I.: Database Dependency Discovery: A Machine Learning Approach. AI Communications 12(3), 139–160 (1999)

    MathSciNet  Google Scholar 

  7. Wyss, C.M., Giannella, C.M., Robertson, E.L.: FastFDs: A Heuristic-Driven, Depth-First Algorithm for Mining Functional Dependencies from Relation Instances. In: Kambayashi, Y., Winiwarter, W., Arikawa, M. (eds.) DaWaK 2001. LNCS, vol. 2114, pp. 101–110. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  8. He, Q., Link, T.W.: Extending Inferring Functional Dependencies in Schema Transformation. In: ACM 2004 (2004)

    Google Scholar 

  9. Montgomery, D.C.: Design and Analysis of Experiments, 5th edn. Wiley (2001)

    Google Scholar 

  10. Savnik, I., Flach, P.: Bottom-up induction of functional dependencies from relations. In: Piatetsky-Shapiro, G. (ed.) Knowledge Discovery in Databases, Papers from the 1993 AAAI Workshop (KDD 1993), Washington, DC, pp. 174–185. AAAI Press (1993)

    Google Scholar 

  11. Mannila, H., Raiha, K.-J.: Algorithms for inferring functional dependencies. Data & Knowledge Engineering 12, 83–99 (1994)

    Article  MATH  Google Scholar 

  12. Bell, S., Brockhausen, P.: Discovery of Data Dependencies in Relational Databases. Technical Report LS-8 Report-14, University of Dortmund (1995)

    Google Scholar 

  13. Kivinen, J., Mannila, H.: Approximate dependency inference from relations. Theor. Comp. Sci. 149, 129–149 (1995)

    Article  MATH  MathSciNet  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Amrita Vishwa Vidyapeetham, Clappana P.O, Kollam, India

    Sandhya Harikumar & R. Reethima

Authors
  1. Sandhya Harikumar
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  2. R. Reethima
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Corresponding author

Correspondence to Sandhya Harikumar .

Editor information

Editors and Affiliations

  1. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

  2. Indian Institute of Information Technology and Management- - Kerala (IIITM-K), Trivandrum, Kerala, India

    Sabu M. Thampi

  3. Faculty of Design, Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  4. Department of Information Systems and Operations Management, University of Florida, Warrington College of Business, Florida, Florida, USA

    Selwyn Piramuthu

  5. University of Applied Sciences, Institute for Information Systems, Olten, Switzerland

    Thomas Hanne

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© 2015 Springer International Publishing Switzerland

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Harikumar, S., Reethima, R. (2015). A Method to Induce Indicative Functional Dependencies for Relational Data Model. In: El-Alfy, ES., Thampi, S., Takagi, H., Piramuthu, S., Hanne, T. (eds) Advances in Intelligent Informatics. Advances in Intelligent Systems and Computing, vol 320. Springer, Cham. https://doi.org/10.1007/978-3-319-11218-3_40

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  • DOI: https://doi.org/10.1007/978-3-319-11218-3_40

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11217-6

  • Online ISBN: 978-3-319-11218-3

  • eBook Packages: EngineeringEngineering (R0)

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