What is it about?
The existing data integration systems aim at integrating either incomplete or uncertain data without identifying the different types of each nature of the information. This paper presentes an intelligent data integration approach, proving cooperative answers that best meet the user requirements. To examine the efﬁciency and effectiveness of our proposed approach, we have developed the fuzzy mediator system and performed extensive experiments. The results prove that the approach improves data integration performance when the incompleteness and uncertainty problems are available independently or simultaneously.
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Why is it important?
The uncertain and incomplete information are two existing information’s natures together in the data source: Dealing with data uncertainty by removing records with uncertain information leads to incomplete query results. In contrast, the incomplete information in the data source allows us to insert inaccurate or uncertain information for completing the data lacking. The proposed approach provides intelligent data integration, enabling efficient generation of cooperative answers from similar ones, retrieved by mediator system.
Read the Original
This page is a summary of: Intelligent data integration from heterogeneous relational databases containing incomplete and uncertain information, Intelligent Data Analysis, January 2022, IOS Press, DOI: 10.3233/ida-205535.
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