A Probabilistic Data Fusion Modeling Approach for Extracting True Values from Uncertain and Conflicting Attributes

A Probabilistic Data Fusion Modeling Approach for Extracting True Values from Uncertain and Conflicting Attributes

Real-world data obtained from integrating heterogeneous data sources are often multi-valued, uncertain, imprecise, error-prone, outdated, and have different degrees of accuracy and correctness. It is critical to resolve data uncertainty and conflicts to present quality data that reflect actual world...

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Bibliographic Details
Main Authors: Ashraf Jaradat, Fadi Safieddine, Aziz Deraman, Omar Ali, Ahmad Al-Ahmad, Yehia Ibrahim Alzoubi
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Big Data and Cognitive Computing
Subjects:
data integration
data accuracy
data conflict
data fusion
probabilistic integration
possible worlds
Online Access:https://www.mdpi.com/2504-2289/6/4/114

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