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cs.DB2026

Strength Is Not Value: Rethinking Approximate Functional Dependency Measures for Error Detection

Xiaolong Wan, Xixian Han

Approximate functional dependency (AFD) strength measures are commonly used to prioritize candidate dependencies, including when selected dependencies support downstream tasks such…

cs.DB2026

Efficient discovery of unique column combinations on disk-resident data with limited memory

Xiaolong Wan, Xixian Han

The discovery of unique column combinations (UCCs) is a core task in data profiling, describing the key constraints of a table. The existing algorithms cannot deal with large-scale…

cs.DB2026

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…

cs.DB2026

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…

cs.DB2026

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-…

cs.DB2026

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…

cs.DB2026

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…

cs.DB2026

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…

cs.DB2025

PAT: Pattern-Perceptive Transformer for Error Detection in Relational Databases

Jian Fu, Xixian Han, Xiaolong Wan +1

Error detection in relational databases is critical for maintaining data quality and is fundamental to tasks such as data cleaning and assessment. Current error detection studies m…