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Evidence Based Conflict Resolution for Independent Sources and Independent Attributes

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Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery (BDAS 2015, BDAS 2016)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 613))

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Abstract

The gigantic use of digital information has changed comprehensively the way we live. People rely more and more on information collected from various sources in every aspect of life. However, due to the natural variety and autonomy of these sources, finding relevant and accurate information is becoming increasingly difficult. Indeed, several sources can provide different conflicting facts for the same real-world object. Moreover, most modern-day applications often provide imperfect information. Therefore, it is strenuous to distinguish the true facts from the false ones. To deal with this problem, we propose in this paper a new evidential conflict resolution method for independent sources and independent attributes. Our method exploits the power of Dempster-Shafer theory so as to find the most trustable facts when data sources provide imperfect information.

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References

  1. Aydin, B.I., Yilmaz, Y.S., Li, Y., Li, Q., Gao, J., Demirbas, M.: Crowdsourcing for multiple-choice question answering (2014)

    Google Scholar 

  2. Dempster, A.: Upper and lower probabilities induced by a multivalued mapping. Ann. Math. Stat. 38(2), 325–339 (1967)

    Article  MathSciNet  MATH  Google Scholar 

  3. Dong, X.L., Gabrilovich, E., Heitz, G., Horn, W., Murphy, K., Sun, S., Zhang, W.: From data fusion to knowledge fusion. Proc. VLDB Endowment 7(10), 881–892 (2014)

    Article  Google Scholar 

  4. Dong, X.L., Saha, B., Srivastava, D.: Less is more: selecting sources wisely for integration. Proc. VLDB Endowment 6(2), 37–48 (2012)

    Article  Google Scholar 

  5. Elouedi, Z., Mellouli, K., Smets, P.: Assessing sensor reliability for multisensor data fusion within the transferable belief model. IEEE Trans. Syst. Man Cybern. Part B Cybern. 34(1), 782–787 (2004)

    Article  MATH  Google Scholar 

  6. Galland, A., Abiteboul, S., Marian, A., Senellart, P.: Corroborating information from disagreeing views. In: Proceedings of the Third ACM International Conference on Web Search and Data Mining, pp. 131–140. ACM (2010)

    Google Scholar 

  7. Jousselme, A.L., Grenier, D., Bossé, É.: A new distance between two bodies of evidence. Inf. Fusion 2(2), 91–101 (2001)

    Article  Google Scholar 

  8. Lee, S.K.: Imprecise and uncertain information in databases: an evidential approach. In: Proceedings of the Eighth International Conference on Data Engineering, 1992, pp. 614–621. IEEE (1992)

    Google Scholar 

  9. Li, Q., Li, Y., Gao, J., Zhao, B., Fan, W., Han, J.: Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation. In: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, pp. 1187–1198. ACM (2014)

    Google Scholar 

  10. Li, Y., Gao, J., Meng, C., Li, Q., Su, L., Zhao, B., Fan, W., Han, J.: A survey on truth discovery. arXiv preprint (2015). arXiv:1505.02463

  11. Sentz, K., Ferson, S.: Combination of evidence in dempster-shafer theory. Technical report, Sandia National Labs., Albuquerque, NM (US); Sandia National Labs., Livermore, CA (US) (2002)

    Google Scholar 

  12. Shafer, G.: A Mathematical Theory of Evidence, vol. 1. Princeton University Press, Princeton (1976)

    MATH  Google Scholar 

  13. Smets, P.: Decision making in the TBM: the necessity of the pignistic transformation. Int. J. Approximate Reasoning 38(2), 133–147 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  14. Waguih, D.A., Berti-Equille, L.: Truth discovery algorithms: an experimental evaluation. arXiv preprint (2014). arXiv:1409.6428

  15. Wang, D., Amin, M.T., Li, S., Abdelzaher, T., Kaplan, L., Gu, S., Pan, C., Liu, H., Aggarwal, C.C., Ganti, R., et al.: Using humans as sensors: an estimation-theoretic perspective. In: Proceedings of the 13th International Symposium on Information Processing in Sensor Networks, pp. 35–46. IEEE Press (2014)

    Google Scholar 

  16. Yin, X., Han, J., Yu, P.S.: Truth discovery with multiple conflicting information providers on the web. IEEE Trans. Knowl. Data Eng. 20(6), 796–808 (2008)

    Article  Google Scholar 

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Authors and Affiliations

  1. Faculty of Cybernetics, Military University of Technology, Warsaw, Poland

    Walid Cherifi & Bolesław Szafrański

Authors
  1. Walid Cherifi
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  2. Bolesław Szafrański
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Corresponding author

Correspondence to Walid Cherifi .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Dariusz Mrozek

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Paweł Kasprowski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Daniel Kostrzewa

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© 2016 Springer International Publishing Switzerland

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Cherifi, W., Szafrański, B. (2016). Evidence Based Conflict Resolution for Independent Sources and Independent Attributes. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Advanced Technologies for Data Mining and Knowledge Discovery. BDAS BDAS 2015 2016. Communications in Computer and Information Science, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-34099-9_41

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  • DOI: https://doi.org/10.1007/978-3-319-34099-9_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-34098-2

  • Online ISBN: 978-3-319-34099-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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