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Encyclopedia of Database Systems pp 2837–2839Cite as

Probabilistic Entity Resolution

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Synonyms

Deduplication; Linkage; Matching

Definition

Entity Resolution is the task of analyzing a collection of data (e.g., database, data set) in order to create entities by merging the data instances that describe the same real-world objects. Uncertain entity resolution is a group of resolution methodologies focusing on handling the uncertainties that are present either in the data or are generated during the resolution process.

Historical Background

The fundamental component of resolution techniques is an instance that provides some characteristic of a real-world object. An instance is a tuple with k attributes 〈v1, …, vk〉, with each attribute being one characteristic of the corresponding object. Consider now a collection of instances. The goal of resolution is to detect the instances that describe the same real-world objects and merge them into entities, i.e., create entity e for representing instances r1, r2, and r3.

The initial resolution approaches focused on handling the...

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Recommended Reading

  1. Andritsos P, Fuxman A, Miller R. Clean answers over dirty databases: a probabilistic approach. In: Proceedings of the 22nd International Conference on Data Engineering; 2006.

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  2. Beskales G, Soliman M, Ilyas I, Ben-David S. Modeling and querying possible repairs in duplicate detection. Proc VLDB Endow. 2009;2(1):598–609.

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  3. Dong XL, Halevy A, Yu C. Data integration with uncertainty. In: Proceedings of the 33rd International Conference on Very Large Data Bases; 2007. p. 687–98.

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  4. Elmagarmid A, Ipeirotis P, Verykios V. Duplicate record detection: a survey. IEEE Trans Knowl Data Eng. 2007;19(1):1–16.

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  5. Ioannou E, Nejdl W, Niederée C, Velegrakis Y. On-the-fly entity-aware query processing in the presence of linkage. Proc VLDB Endow. 2010;3(1):429–38.

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  6. Ioannou E, Staworko S. Management of inconsistencies in data integration. In: Data exchange, integration, and streams. 2013. p. 217–25.

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  7. Re C, Dalvi N, Suciu D. Efficient top-k query evaluation on probabilistic data. In: Proceedings of the 23rd International Conference on Data Engineering; 2007. p. 886–95.

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Author information

Authors and Affiliations

  1. Faculty of Pure and Applied Sciences, Open University of Cyprus, Nicosia, Cyprus

    Ekaterini Ioannou

Authors
  1. Ekaterini Ioannou
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Corresponding author

Correspondence to Ekaterini Ioannou .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, GA, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, ON, Canada

    M. Tamer Özsu

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Ioannou, E. (2018). Probabilistic Entity Resolution. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_80805

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