2020 | OriginalPaper | Buchkapitel
Taking Advantage of Highly-Correlated Attributes in Similarity Queries with Missing Values
verfasst von : Lucas Santiago Rodrigues, Mirela Teixeira Cazzolato, Agma Juci Machado Traina, Caetano Traina Jr.
Erschienen in: Similarity Search and Applications
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Abstract
SOLID
approach to allow similarity queries in complex databases without the need neither of data imputation nor deletion. First, SOLID
finds highly-correlated metric spaces. Then, SOLID
uses a weighted distance function to search by similarity over tuples of complex objects using compatibility factors among metric spaces. Experimental results show that SOLID
outperforms imputation methods with different missing rates. SOLID
was up to \(7.3\%\) better than the competitors in quality when querying over incomplete tuples, reducing \(16.42\%\) the error of similarity searches over incomplete data, and being up to 30.8 times faster than the closest competitor.