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Filtering by: Creator Vergara, Hector A. Remove constraint Creator: Vergara, Hector A. Contributor advisor sim Termehchy, Arash Remove constraint Contributor advisor sim: Termehchy, Arash Committee Member Guo, Ren Remove constraint Committee Member: Guo, Ren

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  • Relational Learning over Dirty Data Using Data Constraints

    Creator:
    Lee, Ga Young
    Abstract:
    Real-world datasets are dirty and contain many errors. Examples of these issues are violations of integrity constraints, duplicates, and inconsistencies in representing data values and entities. Applying machine learning on dirty databases may lead to inaccurate results. Users have to spend a lot of time and effort repairing data errors...
    Resource Type:
    Masters Thesis
    Full Text:
    databases may lead to inaccurate results. Users have to spend a great deal of time and effort repairing