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Multiset Merging: The Majority Rule

  • Conference paper
Eurofuse 2011

Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 107))

Abstract

A well known problem that many sources of data nowadays cope with, is the problem of duplicate data. In general, we can represent a data source as a collection of objects. Deduplication then consists of two main problems: (a) finding duplicate objects and (b) processing those duplicate objects. This paper contributes to the study of the latter problem by investigating functions that map a multiset of objects to a single object. Such functions are called merge functions.We investigate the specific case where an object itself is a multiset. An interesting application of this case is the problem of multiple document summarization. Next to the basic definition of such merge functions, we focus on an important property borrowed from the (more general) field of information fusion: the majority rule.

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References

  1. Elmagarmid, A., Ipeirotis, P., Verykios, V.: Duplicate record detection: A survey. IEEE Transactions on Knowledge and Data Engineering 19(1), 1–16 (2007)

    Article  Google Scholar 

  2. Bronselaer, A., De Tré, G.: Aspects of object merging. In: Proceedings of the NAFIPS Conference, Toronto, Canada, pp. 27–32 (2010)

    Google Scholar 

  3. Bronselaer, A., De Tré, G.: Properties of possibilistic string comparison. IEEE Transactions on Fuzzy Systems 18(2), 312–325 (2010)

    Article  Google Scholar 

  4. Schweizer, B., Sklar, A.: Probabilistic metric spaces. Elsevier, Amsterdam (1983)

    MATH  Google Scholar 

  5. Fellegi, I., Sunter, A.: A theory for record linkage. American Statistical Association Journal 64(328), 1183–1210 (1969)

    Article  Google Scholar 

  6. Lin, J., Mendelzon, A.: Knowledge base merging by majority. In: Dynamic Worlds: From the Frame Problem to Knowledge Management. Kluwer, Dordrecht (1994)

    Google Scholar 

  7. Ricardo, B.-Y., Berthier, R.-N.: Modern information retrieval. ACM Press, New York (1999)

    Google Scholar 

  8. Yager, R.: On the theory of bags. International Journal of General Systems 13(1), 23–27 (1986)

    Article  MathSciNet  Google Scholar 

  9. Konieczny, S., Pérez, R.: Merging information under constraints: a logical framework. Journal of Logic and Computation 12(1), 111–120 (2002)

    Google Scholar 

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© 2011 Springer-Verlag Berlin Heidelberg

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Bronselaer, A., De Tré, G., Van Britsom, D. (2011). Multiset Merging: The Majority Rule. In: Melo-Pinto, P., Couto, P., Serôdio, C., Fodor, J., De Baets, B. (eds) Eurofuse 2011. Advances in Intelligent and Soft Computing, vol 107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24001-0_26

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  • DOI: https://doi.org/10.1007/978-3-642-24001-0_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24000-3

  • Online ISBN: 978-3-642-24001-0

  • eBook Packages: EngineeringEngineering (R0)

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