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In this paper we present GDR, a Guided Data Repair framework that incorporates user feedback in the cleaning process to enhance and accelerate existing automatic repair techniques while minimizing user involvement. GDR consults the user on the updates that are most likely to be beneficial in improving data quality. GDR also uses machine learning methods to identify and apply the correct updates directly to the database without the actual involvement of the user on these specific updates. Todoi:10.14778/1952376.1952378 fatcat:zvm3hh47mvcllhdeomtqqtfrku