An introduction to duplicate detection
By: Felix Naumann, Melanie Herschel
Contributors: Herschel, Melanie
Series: Synthesis lectures on data management -- # 3
Publisher: Morgan & Claypool; Morgan & Claypool Publishers
Published: 2010
Place of publication: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA)
Language: eng
Format: [electronic resource] /
Number of pages: 77
ISBN-13: 9781608452217; 9781608452200
Subjects: Statistical matching; Quality control; Database management; Databases
Other titles: Synthesis digital library of engineering and computer science.
Description: With the ever increasing volume of data, data quality problems abound. Multiple, yet different representations of the same real-world objects in data, duplicates, are one of the most intriguing data quality problems. The effects of such duplicates are detrimental; for instance, bank customers can obtain duplicate identities, inventory levels are monitored incorrectly, catalogs are mailed multiple times to the same household, etc. Automatically detecting duplicates is difficult: First, duplicate representations are usually not identical but slightly differ in their values. Second, in principle all pairs of records should be compared, which is infeasible for large volumes of data. This lecture examines closely the two main components to overcome these difficulties: (i) Similarity measures are used to automatically identify duplicates when comparing two records.Well-chosen similarity measures 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.
Notes: Part of: Synthesis digital library of engineering and computer science.

Title from PDF t.p. (viewed on April 7, 2010).

Series from website.

Includes bibliographical references (p. 71-76).

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

Also available in print.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.
Table of contents: title: 1. Data cleansing: introduction and motivation; title: Data quality; title: Data quality dimensions; title: Data cleansing; title: Causes for duplicates; title: Intra-source duplicates; title: Inter-source duplicates; title: Use cases for duplicate detection; title: Customer relationship management; title: Scientific databases; title: Data spaces and linked open data; title: Lecture overview; title: 2. Problem definition; title: Formal definition; title: Complexity analysis; title: Data in complex relationships; title: Data model; title: Challenges of data with complex relationships; title: 3. Similarity functions; title: Token-based similarity; title: Jaccard coefficient; title: Cosine similarity using token frequency and inverse document frequency; title: Similarity based on tokenization using q-grams; title: Edit-based similarity; title: Edit distance measures; title: Jaro and Jaro-Winkler distance; title: Hybrid functions; title: Extended Jaccard similarity; title: Monge-Elkan measure; title: Soft TF/IDF; title: Measures for data with complex relationships; title: Other similarity measures; title: Rule-based record comparison; title: Equational theory; title: Duplicate profiles; title: 4. Duplicate detection algorithms; title: Pairwise comparison algorithms; title: Blocking; title: Sorted-neighborhood; title: Comparison; title: Algorithms for data with complex relationships; title: Hierarchical relationships; title: Relationships forming a graph; title: Clustering algorithms; title: Clustering based on the duplicate pair graph; title: Clustering adjusting to data & cluster characteristics; title: 5. Evaluating detection success; title: Precision and recall; title: Data sets; title: Real-world data sets; title: Synthetic data sets; title: Towards a duplicate detection benchmark; title: 6. Conclusion and outlook; title: Bibliography; title: Authors' biographies.