Titlebook: An Introduction to Duplicate Detection; Felix Naumann,Melanie Herschel Book 2010 Springer Nature Switzerland AG 2010

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Data Cleansing: Introduction and Motivation, sources, data quality problems abound. One of the most intriguing data quality problems is that of multiple, yet different representations of the same real-world object in the data. For instance, an individual might be represented multiple times in a customer database, a single product might be lis

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Evaluating Detection Success,nd. Difficulties that prevent a benchmark data set are privacy and confidentiality concerns regarding the data. In this section, we first describe standard measures for success, in particular precision and recall. We then proceed to discuss existing data sets and data generators.

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Conclusion and Outlook,. Duplicates appear in many data sets, from customer records and business transactions to scientific databases and Wikipedia entries. The problem definition — finding multiple representations of the same real world object — is concise, crisp, and clear, but it is comprised of two very difficult prob

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Book 2010res improve the effectiveness of duplicate detection. (ii) Algorithms are developed to perform on very large volumes of data in search for duplicates. Well-designed algorithms improve the efficiency of duplicate detection. Finally, we discuss methods to evaluate the success of duplicate detection. T

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