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Duplicate record detection: A survey

delete2007-01-01
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Ahmed K. Elmagarmid *
P
Panagiotis G. Ipeirotis
V
Vassilios S. Verykios
DOI:10.1109/TKDE.2007.250581delete
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摘要

摘要

En 中文
Often, in the real world, entities have two or more representations in databases. Duplicate records do not share a common key and/or they contain errors that make duplicate matching a difficult task. Errors are introduced as the result of transcription errors, incomplete information, lack of standard formats, or any combination of these factors. In this paper, we present a thorough analysis of the literature on duplicate record detection. We cover similarity metrics that are commonly used to detect similar field entries, and we present an extensive set of duplicate detection algorithms that can detect approximately duplicate records in a database. We also cover multiple techniques for improving the efficiency and scalability of approximate duplicate detection algorithms. We conclude with coverage of existing tools and with a brief discussion of the big open problems in the area.
Keyword:
duplicate detection
data cleaning
data integration
record linkage
data deduplication
instance identification
database hardening
name matching
identity uncertainty
entity resolution
fuzzy duplicate detection
entity matching
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IEEE Transactions on Knowledge and Data Engineering 封面图
IEEE Transactions on Knowledge and Data Engineering
IF:
10.4
论文数:
6.8K
被引数:
3.2W

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