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Discovery of Temporal Graph Functional...
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Discovery of Temporal Graph Functional Dependencies

Abstract

Temporal Graph Functional Dependencies (TGFDs) are a class of data quality rules imposing topological, attribute dependency constraints over a period of time. To make TGFDs usable in practice, we study the TGFD discovery problem, and show the satisfiability, implication, and validation problems for k-bounded TGFDs are in PTIME. We introduce the TGFDMiner algorithm, which discovers minimal, frequent TGFDs. Our evaluation shows the efficiency and …

Authors

Noronha L; Chiang F

Pagination

pp. 3348-3352

Publisher

Association for Computing Machinery (ACM)

Publication Date

October 26, 2021

DOI

10.1145/3459637.3482087

Name of conference

Proceedings of the 30th ACM International Conference on Information & Knowledge Management