@inproceedings{36798bf7838a4c6db18b3edbf57772f5,
title = "T-REx: Table Repair Explanations",
abstract = "Data repair is a common and crucial step in many frameworks today, as applications may use data from different sources and of different levels of credibility. Thus, this step has been the focus of many works, proposing diverse approaches. To assist users in understanding the output of such data repair algorithms, we propose T-REx, a system for providing data repair explanations through Shapley values. The system is generic and not specific to a given repair algorithm or approach: it treats the algorithm as a black box. Given a specific table cell selected by the user, T-REx employs Shapley values to explain the significance of each constraint and each table cell in the repair of the cell of interest. T-REx then ranks the constraints and table cells according to their importance in the repair of this cell. This explanation allows users to understand the repair process, as well as to act based on this knowledge, to modify the most influencing constraints or the original database.",
keywords = "data repairs, database constraints, shapley value",
author = "Daniel Deutch and Nave Frost and Amir Gilad and Oren Sheffer",
note = "Publisher Copyright: {\textcopyright} 2020 Association for Computing Machinery.; 2020 ACM SIGMOD International Conference on Management of Data, SIGMOD 2020 ; Conference date: 14-06-2020 Through 19-06-2020",
year = "2020",
month = jun,
day = "14",
doi = "10.1145/3318464.3384700",
language = "الإنجليزيّة",
series = "Proceedings of the ACM SIGMOD International Conference on Management of Data",
publisher = "Association for Computing Machinery",
pages = "2765--2768",
booktitle = "SIGMOD 2020 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data",
address = "الولايات المتّحدة",
}