Robust Entity Resolution using Random Graphs

Sainyam Galhotra · Donatella Firmani · Barna Saha · Divesh Srivastava

24 citations0/0 files storedACM SIGMOD International Conference on Management of Data (SIGMOD)

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Data Quality and Management Advanced Database Systems and Queries Machine Learning and Data Classification

Abstract

Entity resolution (ER) seeks to identify which records in a data set refer to the same real-world entity. Given the diversity of ways in which entities can be represented, matched and distinguished, ER is known to be a challenging task for automated strategies, but relatively easier for expert humans. In our work, we abstract the knowledge of experts with the notion of a binary oracle. Our oracle can answer questions of the form "do records u and v refer to the same entity?" under a flexible error model, allowing for some questions to be more difficult to answer correctly than others.

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References

1969A Theory for Record Linkage 2006Duplicate Record Detection: A Survey 2012CrowdER 2012Entity resolution 2009Entity resolution with iterative blocking 2008Febrl -2012Pay-As-You-Go Entity Resolution 2014Crowdsourcing algorithms for entity resolution

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