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Data Fusion

期刊

ACM COMPUTING SURVEYS
卷 41, 期 1, 页码 -

出版社

ASSOC COMPUTING MACHINERY
DOI: 10.1145/1456650.1456651

关键词

Algorithms; Languages; Data cleansing; data conflicts; data consolidation; data integration; data merging; data quality

资金

  1. German Research Society (DFG) [NA 432]

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The development of the Internet in recent years has made it possible and useful to access many different information systems anywhere in the world to obtain information. While there is much research on the integration of heterogeneous information systems, most commercial systems stop short of the actual integration of available data. Data fusion is the process of fusing multiple records representing the same real-world object into a single, consistent, and clean representation. This article places data fusion into the greater context of data integration, precisely defines the goals of data fusion, namely, complete, concise, and consistent data, and highlights the challenges of data fusion, namely, uncertain and conflicting data values. We give an overview and classification of different ways of fusing data and present several techniques based on standard and advanced operators of the relational algebra and SQL. Finally, the article features a comprehensive survey of data integration systems from academia and industry, showing if and how data fusion is performed in each.

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