TY  - JOUR
A1  - Berti-Equille, Laure
A1  - Harmouch, Nazar
A1  - Naumann, Felix
A1  - Novelli, Noel
A1  - Saravanan, Thirumuruganathan
T1  - Discovery of genuine functional dependencies from relational data with missing values
JF  - Proceedings of the VLDB Endowment
N2  - Functional dependencies (FDs) play an important role in maintaining data quality. They can be used to enforce data consistency and to guide repairs over a database. In this work, we investigate the problem of missing values and its impact on FD discovery. When using existing FD discovery algorithms, some genuine FDs could not be detected precisely due to missing values or some non-genuine FDs can be discovered even though they are caused by missing values with a certain NULL semantics. We define a notion of genuineness and propose algorithms to compute the genuineness score of a discovered FD. This can be used to identify the genuine FDs among the set of all valid dependencies that hold on the data. We evaluate the quality of our method over various real-world and semi-synthetic datasets with extensive experiments. The results show that our method performs well for relatively large FD sets and is able to accurately capture genuine FDs.
Y1  - 2018
U6  - https://doi.org/10.14778/3204028.3204032
SN  - 2150-8097
VL  - 11
IS  - 8
SP  - 880
EP  - 892
PB  - Association for Computing Machinery
CY  - New York
ER  -