Entity Information Life Cycle for Big Data: Master Data Management and Information Integration by John R. Talburt & Yinle Zhou

Entity Information Life Cycle for Big Data: Master Data Management and Information Integration by John R. Talburt & Yinle Zhou

Author:John R. Talburt & Yinle Zhou [Talburt, John R.]
Language: eng
Format: azw3
ISBN: 9780128006658
Publisher: Elsevier Science
Published: 2015-04-19T16:00:00+00:00


Frequency-based Weights and the Scoring Rule

One further refinement of estimating pattern weight from attribute weights is called frequency-based weights. Frequency-based weighting is simply a reinterpretation of the probability mi and ui from agreement on attributes to agreement on specific attribute values. Thus, if v is a value of the i-th identity attribute then

mi(v) = probability equivalent references agree on the value v in attribute i

ui(v) = probability nonequivalent references agree on the value v in attribute i



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