Ranking for data repairs

Abstract— Improving data quality is a time-consuming, laborintensive and often domain specific operation. A recent principled approach for repairing dirty database is to use data quality rules in the form of database constraints to identify dirty tuples and then use the rules to derive data repairs. Most of existing data repair approaches focus on providing fully automated solutions, which could be risky to depend upon especially for critical data. To guarantee the optimal quality repairs applied to the database, users should be involved to confirm each repair. This highlights the need for an interactive approach that combines the best of both; automatically generating repairs, while efficiently employing user’s efforts to verify the repairs. In such approach, the user will guide an online repairing process to incrementally generate repairs. A key challenge in this approach is the response time within the user’s interactive sessions, because the process of generating the repai...

• Type: Conference
• Year: 2010
• Where: ICDE
• Authors: Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Neville
• Keywords: Data Quality, Data Quality Rules, Database, ICDE 2010, Repairs