8 papers
EviDC: A Violation-Guided Algorithm for Incremental Denial Constraint Discovery
Qian Zhou, Xixian Han, Xiaolong Wan
Denial Constraints (DCs) are an important class of integrity constraints and have been widely used in data quality management. In dynamic datasets, newly inserted tuples may invali…
Not Every Dependency Is Worth Discovering: Toward Value-Driven Data Dependency Discovery
Xiaolong Wan, Xixian Han
Data dependency discovery has traditionally focused on identifying dependencies that hold in the data or are statistically strong. Yet a dependency may be valid without being valua…
Top-k Approximate Functional Dependency Discovery
Xiaolong Wan, Xixian Han
Approximate functional dependencies (AFDs) relax exact functional dependencies by tolerating a bounded degree of violation, making them suited for data quality auditing. Threshold-…
Topology-Aware Subset Repair via Entropy-Guided Density and Graph Decomposition
Guoqi Zhao, Xixian Han, Xiaolong Wan
Subset repair is an important data cleaning technique that enforces integrity constraints by deleting a minimal number of conflicting tuples, yet multiple minimal repairs often exi…
EAIFD: A Fast and Scalable Algorithm for Incremental Functional Dependency Discovery
Yajuan Xu, Xixian Han, Xiaolong Wan
Functional dependencies (FDs) are fundamental integrity constraints in relational databases, but discovering them under incremental updates remains challenging. While static algori…
Redundancy-Driven Top- Functional Dependency Discovery
Xiaolong Wan, Xixian Han
Functional dependencies (FDs) are basic constraints in relational databases and are used for many data management tasks. Most FD discovery algorithms find all valid dependencies, b…